{ "schema_version": 1, "language": "en", "imported": "2026-10-15", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "sha256": "f348cfd4fa6deccd128cbda11fc3a433bdbc260e6d748a415549ec66b47d43c2", "selected_regular_files": 471, "skill_files_present": false, "unique_required_skills": 82, "role_manifest_mismatches": [] }, "profiles": [ { "id": "prof-account-executive", "name": "Account Executive (B2B sales, deals, pipeline)", "description": "Owns revenue from qualified leads to signed deals: discovery, solution fit, proposals and pricing within policy, negotiation, closing and handover to delivery; keeps an honest pipeline and forecasts from evidence", "category": "sales", "category_name": "Sales", "family": "commercial", "family_name": "Commercial work", "adaptation_state": "described", "tasks": [ "Owns revenue from qualified leads to signed deals: discovery, solution fit, proposals and pricing within policy, negotiation, closing and handover to delivery; keeps an honest pipeline and forecasts from evidence" ], "methods": [ "Needs discovery and evidence-based pipeline review" ], "outputs": [ "Proposal and documented handover" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "openpyxl", "pandas", "python-docx" ], "required_skills": [ "skill-business-writing", "skill-business-analysis", "skill-email-triage", "skill-contract-review" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-account-executive/professional.json", "source_id": "prof-account-executive", "source_version": "1.0.0", "source_lifecycle": "published", "manifest_sha256": "de3ed37c9903260b5275b1ed2f04dcd8dcb96117a7f5fd4f272277b921f00929", "role_sha256": "3cd43544956a6b18a006e514d2b6b0001691d32a20ecc52c70fd9e1e5fcb7dad", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "fetch", "searxng" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-accountant", "name": "Accountant / Bookkeeper", "description": "Day-to-day ledger, period close, financial statements per local GAAP/IFRS", "category": "finance", "category_name": "Finance", "family": "finance-legal", "family_name": "Finance and law", "adaptation_state": "described", "tasks": [ "Day-to-day ledger, period close, financial statements per local GAAP/IFRS" ], "methods": [ "Reconciliation, scenario analysis and limit review" ], "outputs": [ "Financial model or report with assumptions" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "matplotlib", "numpy", "openpyxl", "pandas", "python-dateutil", "scipy", "sqlalchemy" ], "required_skills": [ "skill-bookkeeping", "skill-tax-computation", "skill-data-analysis" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-accountant/professional.json", "source_id": "prof-accountant", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "8d9ccef56d1c9d49c4bb3c0e0c6f27dc404e411bd472e55250e9069fe0605fc2", "role_sha256": "f2dab2e0c14e057c81ce81df4c89d2036aa37a85ce7bb6cebe628abfd72ec9c6", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "fetch", "sqlite" ], "optional": [] } }, "related_scenarios": [ "reporting-operation" ] }, { "id": "prof-ai-safety-engineer", "name": "AI Safety / Alignment Engineer", "description": "Eval harnesses, red-teaming LLMs, safety guardrails, bias measurement", "category": "data", "category_name": "Data", "family": "data-ai", "family_name": "Data and AI", "adaptation_state": "described", "tasks": [ "Eval harnesses, red-teaming LLMs, safety guardrails, bias measurement" ], "methods": [ "Data quality checks and reproducible analysis" ], "outputs": [ "Dataset, analysis or model with checks" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "anthropic", "chromadb", "instructor", "langchain", "openai", "ragas", "sentence-transformers", "tiktoken" ], "required_skills": [ "skill-llm-engineering" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-ai-safety-engineer/professional.json", "source_id": "prof-ai-safety-engineer", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "4cd722c498912fc84f4f83cd7ddaffea3caf5e2eaf76e47074c64ffaffddeba4", "role_sha256": "9c8b76879f8a180862e4c681040283460342914a1ad3312930bc4535e0f8b5ff", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "fetch", "github" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-android-engineer", "name": "Android Engineer", "description": "Kotlin / Jetpack Compose, Play Store, Material 3, Google Play Billing", "category": "engineering", "category_name": "Software engineering", "family": "technology", "family_name": "Technology", "adaptation_state": "described", "tasks": [ "Kotlin / Jetpack Compose, Play Store, Material 3, Google Play Billing" ], "methods": [ "Requirements, implementation and testing" ], "outputs": [ "Software change with test evidence" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "@expo/cli", "android-tools-adb", "eas-cli", "openjdk-17-jdk", "react-native-cli" ], "required_skills": [ "skill-mobile-android" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-android-engineer/professional.json", "source_id": "prof-android-engineer", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "865f54442e2adceb33f0f9d86c5a8c25bc9c7ae03744c247870a9068381a0fef", "role_sha256": "fc200dc35994107b6bc60166df73c95db67b6735eb47409d4869d0212c2a3b5c", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "github", "fetch" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-backend-engineer", "name": "Backend Engineer", "description": "API services, DB schema, queue / cache / observability", "category": "engineering", "category_name": "Software engineering", "family": "technology", "family_name": "Technology", "adaptation_state": "described", "tasks": [ "API services, DB schema, queue / cache / observability" ], "methods": [ "Requirements, implementation and testing" ], "outputs": [ "Software change with test evidence" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "@playwright/test", "alembic", "asyncpg", "celery", "cypress", "faker", "fastapi", "httpx", "hypothesis", "postgresql-client", "pydantic", "pytest", "pytest-asyncio", "pytest-xdist", "redis", "redis-tools", "sqlalchemy", "typescript", "uvicorn", "vitest" ], "required_skills": [ "skill-backend-services", "skill-test-automation" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-backend-engineer/professional.json", "source_id": "prof-backend-engineer", "source_version": "1.4.2", "source_lifecycle": "published", "manifest_sha256": "5299c273ff2b50d20662af495718454fce755af5c7ce6a4f3de6b582a0a46505", "role_sha256": "ff12a3f8ca46b4c9f09298323580f398d2c4d884d3a31b0c1b005d17197e1d36", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "github", "postgres", "redis", "fetch" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-banking-specialist", "name": "Banking Systems Specialist", "description": "Retail/commercial banking ops + financial messaging (XBRL, SEPA, ISO 20022, SWIFT MT, FIX)", "category": "finance", "category_name": "Finance", "family": "finance-legal", "family_name": "Finance and law", "adaptation_state": "described", "tasks": [ "Retail/commercial banking ops + financial messaging (XBRL, SEPA, ISO 20022, SWIFT MT, FIX)" ], "methods": [ "Reconciliation, scenario analysis and limit review" ], "outputs": [ "Financial model or report with assumptions" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "arelle-release", "duckdb", "fixparser", "fuzzywuzzy", "numpy", "openpyxl", "pandas", "pycountry", "python-Levenshtein", "python-dateutil", "python-iso20022", "requests", "schwifty", "scikit-learn", "sepaxml", "unidecode" ], "required_skills": [ "skill-financial-systems", "skill-kyc-cdd", "skill-transaction-monitoring", "skill-sanctions-screening", "skill-tax-computation" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-banking-specialist/professional.json", "source_id": "prof-banking-specialist", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "88afade37354378292205ff99dd873eee32874eeeafd71f45b6335f6955ebbb5", "role_sha256": "e19ced6997725d1aa8abd8b261ea952cf7bdd6831e68a0b71848807ff68dd58d", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "fetch", "sqlite" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-bim-coordinator", "name": "BIM Coordinator", "description": "Coordinates model information, disciplines, clashes, issues and delivery requirements", "category": "architecture", "category_name": "Architecture", "family": "built-environment", "family_name": "Built environment", "adaptation_state": "described", "tasks": [ "Coordinates model information, disciplines, clashes, issues and delivery requirements" ], "methods": [ "Requirements and interface coordination" ], "outputs": [ "Coordinated design requirements" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "ifcopenshell", "matplotlib", "numpy", "openpyxl", "pandas", "pandoc", "python-docx", "scipy" ], "required_skills": [ "skill-bim-coordination", "skill-project-controls", "skill-data-analysis" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-bim-coordinator/professional.json", "source_id": "prof-bim-coordinator", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "345508d8322ce5bfa9fae1715c18640abeedaa4de4b238245052e4548c18c5a2", "role_sha256": "06d2579df79db19e06904651ae80259e8028158dca48c890734d1b6d819c6d9d", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-brand-strategist", "name": "Brand / Content Strategist", "description": "Positioning, narrative, content pillars, editorial calendar", "category": "marketing", "category_name": "Marketing", "family": "commercial", "family_name": "Commercial work", "adaptation_state": "described", "tasks": [ "Positioning, narrative, content pillars, editorial calendar" ], "methods": [ "Audience research and measured experiments" ], "outputs": [ "Campaign plan and results analysis" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [], "required_skills": [ "skill-content-writing" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-brand-strategist/professional.json", "source_id": "prof-brand-strategist", "source_version": "1.4.1", "source_lifecycle": "published", "manifest_sha256": "d4f38f576204c09ff5e15f9bc0ccf696aa5d95f7ef97a8f88b5eb94cf087eee9", "role_sha256": "b3dc2ca8c73858821da5db412795ac21751bd8388af10a71bfb5f69bc8fd3f7a", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "fetch", "notion", "google-drive" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-bug-bounty-hunter", "name": "Vulnerability Researcher", "description": "Assesses security within an authorized program scope and prepares findings for remediation.", "category": "security", "category_name": "Defensive security", "family": "cyber-risk", "family_name": "Cyber risk", "adaptation_state": "described", "tasks": [ "Assesses security within an authorized program scope and prepares findings for remediation." ], "methods": [ "Authorized assessment and evidence review" ], "outputs": [ "Defensive findings and remediation plan" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "git", "semgrep" ], "required_skills": [ "skill-security-audit", "skill-code-review" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-bug-bounty-hunter/professional.json", "source_id": "prof-bug-bounty-hunter", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "2e393986afaf9b3055689f9f37af81ea6112cd4ffa4bab2599988d34b6fed9c4", "role_sha256": "e7f4007c497463b184f7d9da7b3eac593ce1f621d353f42f67153a78d7d0cce0", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-building-architect", "name": "Building Architect", "description": "Develops spatial, functional, regulatory and coordinated building design requirements", "category": "architecture", "category_name": "Architecture", "family": "built-environment", "family_name": "Built environment", "adaptation_state": "described", "tasks": [ "Develops spatial, functional, regulatory and coordinated building design requirements" ], "methods": [ "Requirements and interface coordination" ], "outputs": [ "Coordinated design requirements" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "ifcopenshell", "openpyxl", "pandas", "pandoc", "python-docx" ], "required_skills": [ "skill-bim-coordination", "skill-project-controls", "skill-business-writing" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-building-architect/professional.json", "source_id": "prof-building-architect", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "0f9dd8da49f9fb6d2acdf0b4e6b382a237946f48a1ddf904bfba3c289dc51f2d", "role_sha256": "82fa0eb0b86c882f5c193580812851b8f5588326d68e1ae93e7ad6f8db175dab", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-business-analyst", "name": "Business Analyst", "description": "Requirements elicitation, process modeling (BPMN), gap analysis", "category": "product", "category_name": "Product", "family": "business", "family_name": "Business operations", "adaptation_state": "described", "tasks": [ "Requirements elicitation, process modeling (BPMN), gap analysis" ], "methods": [ "User research, prioritization and prototyping" ], "outputs": [ "Requirements, prototype or research findings" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "matplotlib", "numpy", "openpyxl", "pandas", "pandoc", "python-docx", "scipy" ], "required_skills": [ "skill-business-analysis", "skill-data-analysis", "skill-business-writing" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-business-analyst/professional.json", "source_id": "prof-business-analyst", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "b834d27991cb82bac40bf3cc0d171d777d505d17d59b2a800abf1e1a8b309caf", "role_sha256": "fbe702550ab9d03e41c7120325b1a038968033ccbe7d3af39417c19c0d61b08f", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "notion", "postgres", "sqlite", "fetch" ], "optional": [] } }, "related_scenarios": [ "business-discovery" ] }, { "id": "prof-cargo-agent", "name": "Cargo / Freight Agent", "description": "Handles freight requests, carrier communication and quotations.", "category": "logistics", "category_name": "Logistics", "family": "supply-chain", "family_name": "Supply chains", "adaptation_state": "described", "tasks": [ "Handles freight requests, carrier communication and quotations." ], "methods": [ "Constraint-based planning and delivery tracking" ], "outputs": [ "Transport or warehouse plan" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "@google-cloud/local-auth", "google-auth", "google-auth-oauthlib", "googleapis", "pandoc", "poppler-utils", "tesseract-ocr" ], "required_skills": [ "skill-rfq-extraction", "skill-email-triage", "skill-pdf-extraction" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-cargo-agent/professional.json", "source_id": "prof-cargo-agent", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "655c6963f98a40fcfc4f4e689cb02fba303de124123119296858433f4dbf9e79", "role_sha256": "6218bd8b00a3e91ff72ade6da6b7a195b2d99f1dcf8a93e3534cdb97070e986b", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-category-manager", "name": "Procurement Category Manager", "description": "Owns category demand, supplier market, sourcing pipeline, contracts and value delivery", "category": "procurement", "category_name": "Procurement", "family": "supply-chain", "family_name": "Supply chains", "adaptation_state": "described", "tasks": [ "Owns category demand, supplier market, sourcing pipeline, contracts and value delivery" ], "methods": [ "Supplier comparison and obligation review" ], "outputs": [ "Sourcing recommendation with evidence" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "beautifulsoup4", "openpyxl", "pandas", "pandoc", "pdfplumber", "python-docx", "requests" ], "required_skills": [ "skill-strategic-sourcing", "skill-supplier-management", "skill-vendor-due-diligence", "skill-contract-review" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-category-manager/professional.json", "source_id": "prof-category-manager", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "ce7ede801cdefa063bb9544ffa46326554d0a12e233b736618a562ed087536b3", "role_sha256": "f9ef078a0c282c656314ad0ca23b12fcad8c5af393839af2f748a0f4de62c6c3", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-cfo", "name": "CFO / Finance Director", "description": "Financial strategy, controllership, FP&A oversight, capital allocation", "category": "finance", "category_name": "Finance", "family": "finance-legal", "family_name": "Finance and law", "adaptation_state": "described", "tasks": [ "Financial strategy, controllership, FP&A oversight, capital allocation" ], "methods": [ "Reconciliation, scenario analysis and limit review" ], "outputs": [ "Financial model or report with assumptions" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "arelle-release", "fixparser", "openpyxl", "pandas", "pycountry", "python-iso20022", "schwifty", "sepaxml", "sqlalchemy" ], "required_skills": [ "skill-financial-systems", "skill-bookkeeping" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-cfo/professional.json", "source_id": "prof-cfo", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "934374c80526ac61092cbd1da2765d3d392e38f87eddf38189ca1c964194bde1", "role_sha256": "0b90eefc5560633e5d6ef046c4a3434665935c182bb184f3271da804a375c787", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "fetch", "sqlite", "postgres" ], "optional": [] } }, "related_scenarios": [ "existing-business-transition" ] }, { "id": "prof-chief-of-staff", "name": "Chief of Staff (decision flow, priorities, follow-through for the director)", "description": "Force multiplier for the director: turns intent into a prioritised agenda, tracks decisions and commitments to closure, prepares briefs and options, runs the cadence of reviews and keeps the organisation's attention on what matters", "category": "operations", "category_name": "Operations", "family": "business", "family_name": "Business operations", "adaptation_state": "described", "tasks": [ "Force multiplier for the director: turns intent into a prioritised agenda, tracks decisions and commitments to closure, prepares briefs and options, runs the cadence of reviews and keeps the organisation's attention on what matters" ], "methods": [ "Process mapping and exception review" ], "outputs": [ "Operating plan and obligation register" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "openpyxl", "pandas", "python-docx" ], "required_skills": [ "skill-business-writing", "skill-project-controls", "skill-email-triage", "skill-business-analysis" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-chief-of-staff/professional.json", "source_id": "prof-chief-of-staff", "source_version": "1.0.0", "source_lifecycle": "published", "manifest_sha256": "8f152a3899fee019f4d4078d2b54d443b2821a2d4731b56d8cd6e5f10f754734", "role_sha256": "bedabaf067206fdac03e0be39af5b2f94e5db6c8a5dcf45fe467699adaa8361f", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "fetch" ], "optional": [] } }, "related_scenarios": [ "coordination-office" ] }, { "id": "prof-civil-engineer", "name": "Civil Engineer", "description": "Develops and reviews civil infrastructure requirements, calculations and constructability", "category": "architecture", "category_name": "Architecture", "family": "built-environment", "family_name": "Built environment", "adaptation_state": "described", "tasks": [ "Develops and reviews civil infrastructure requirements, calculations and constructability" ], "methods": [ "Requirements and interface coordination" ], "outputs": [ "Coordinated design requirements" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "matplotlib", "numpy", "openpyxl", "pandas", "pandoc", "python-docx", "scipy" ], "required_skills": [ "skill-project-controls", "skill-data-analysis", "skill-business-writing" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-civil-engineer/professional.json", "source_id": "prof-civil-engineer", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "996e4d3efa961ad58c321ea20811cb1ce3308c114cd632955691e9142671a0a0", "role_sha256": "989c79434e783e4215a0d064872f8a0a9ef599780856e1e30d1810729d023ee5", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-clinical-research-coordinator", "name": "Clinical Research Coordinator", "description": "GCP, protocol mgmt, IRB submissions, AE/SAE, source documentation", "category": "compliance", "category_name": "Compliance", "family": "cyber-risk", "family_name": "Cyber risk", "adaptation_state": "described", "tasks": [ "GCP, protocol mgmt, IRB submissions, AE/SAE, source documentation" ], "methods": [ "Requirements mapping and control assessment" ], "outputs": [ "Requirements register and assessment" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "matplotlib", "numpy", "openpyxl", "pandas", "pandoc", "poppler-utils", "python-docx", "scipy", "tesseract-ocr" ], "required_skills": [ "skill-clinical-evidence-operations", "skill-pdf-extraction", "skill-data-analysis" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-clinical-research-coordinator/professional.json", "source_id": "prof-clinical-research-coordinator", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "5eceeadd80cce316113ab93ce3ad6853fafc78bfb347da279335340cff0d0d91", "role_sha256": "355424b5cafbeb791326f8ea3f8eb51d70203e09218e46e5f30285cf89bcd71f", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "fetch" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-cloud-architect", "name": "Cloud / Solutions Architect", "description": "Multi-region AWS / GCP / Azure, Well-Architected, cost optimization", "category": "engineering", "category_name": "Software engineering", "family": "technology", "family_name": "Technology", "adaptation_state": "described", "tasks": [ "Multi-region AWS / GCP / Azure, Well-Architected, cost optimization" ], "methods": [ "Requirements, implementation and testing" ], "outputs": [ "Software change with test evidence" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "aws-cdk", "cdktf", "jq", "kubernetes", "pulumi", "python-terraform", "pyyaml", "unzip" ], "required_skills": [ "skill-iac", "skill-k8s" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-cloud-architect/professional.json", "source_id": "prof-cloud-architect", "source_version": "1.4.1", "source_lifecycle": "published", "manifest_sha256": "d85cda6d59f257a48b93cabbfec6327ddb7f1ebf33349beb3b16978db9825eae", "role_sha256": "c090c3f9c4e9c1e76a764a5d3fe1b651e4de276fe0ee800846618adc61a8cf56", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "github", "postgres", "fetch" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-cmo", "name": "CMO / Chief Marketing Officer", "description": "Brand, demand gen, GTM, positioning, marketing-mix, customer insights", "category": "marketing", "category_name": "Marketing", "family": "commercial", "family_name": "Commercial work", "adaptation_state": "described", "tasks": [ "Brand, demand gen, GTM, positioning, marketing-mix, customer insights" ], "methods": [ "Audience research and measured experiments" ], "outputs": [ "Campaign plan and results analysis" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "matplotlib", "numpy", "openpyxl", "pandas", "scipy" ], "required_skills": [ "skill-marketing-strategy", "skill-data-analysis", "skill-content-writing" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-cmo/professional.json", "source_id": "prof-cmo", "source_version": "1.4.1", "source_lifecycle": "published", "manifest_sha256": "6582d6418967c6351117a1b5a8a50bbc990165aac7651c21ad5d5337baeadcf1", "role_sha256": "88265f6df04ecf482d71ca40a24fb98c7fd31c05acb26271e5c53774a0f16eca", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-community-manager", "name": "Community Manager (members, moderation, programs, feedback loop)", "description": "Builds and runs the organisation's community: onboarding, moderation and rules, programs and events, ambassador and contributor paths, and the feedback loop from members to product and leadership", "category": "marketing", "category_name": "Marketing", "family": "commercial", "family_name": "Commercial work", "adaptation_state": "described", "tasks": [ "Builds and runs the organisation's community: onboarding, moderation and rules, programs and events, ambassador and contributor paths, and the feedback loop from members to product and leadership" ], "methods": [ "Audience research and measured experiments" ], "outputs": [ "Campaign plan and results analysis" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "matplotlib", "pandas" ], "required_skills": [ "skill-business-writing", "skill-content-writing", "skill-email-triage" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-community-manager/professional.json", "source_id": "prof-community-manager", "source_version": "1.0.0", "source_lifecycle": "published", "manifest_sha256": "8bca534956e6ba148fee42e22478b915526d7a846b7a9057baa61152dff2ca86", "role_sha256": "5c32f9f307ae81a2340da49a048a169c478bc69a19ea7b2a99abd3d529893591", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "fetch" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-compliance-officer", "name": "Compliance Officer (general)", "description": "Policy framework, control self-assessment, regulatory horizon scanning, training", "category": "compliance", "category_name": "Compliance", "family": "cyber-risk", "family_name": "Cyber risk", "adaptation_state": "described", "tasks": [ "Policy framework, control self-assessment, regulatory horizon scanning, training" ], "methods": [ "Requirements mapping and control assessment" ], "outputs": [ "Requirements register and assessment" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "beautifulsoup4", "duckdb", "fuzzywuzzy", "openpyxl", "pandas", "pandoc", "pdfplumber", "python-Levenshtein", "python-docx", "requests", "unidecode" ], "required_skills": [ "skill-internal-controls", "skill-vendor-due-diligence", "skill-sanctions-screening", "skill-contract-review" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-compliance-officer/professional.json", "source_id": "prof-compliance-officer", "source_version": "1.5.0", "source_lifecycle": "published", "manifest_sha256": "0e324498493c42c0b68f859334463957d86384d87d53d3c2cedcfa3f26cdeaa4", "role_sha256": "0666589059ff7c017321c3f3b4f9295521b5576d94feeaa7651f7e40f3ebf9e4", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "fetch", "searxng", "brave-search" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-construction-attorney", "name": "Construction Law Attorney", "description": "Contracts (AIA / FIDIC), liens, claims, delay, surety, OSHA", "category": "legal", "category_name": "Legal materials", "family": "finance-legal", "family_name": "Finance and law", "adaptation_state": "described", "tasks": [ "Contracts (AIA / FIDIC), liens, claims, delay, surety, OSHA" ], "methods": [ "Source review, issue mapping and document preparation" ], "outputs": [ "Draft for an authorized specialist" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "beautifulsoup4", "lxml", "pandoc", "pdfplumber", "python-docx", "requests" ], "required_skills": [ "skill-legal-research", "skill-contract-review" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-construction-attorney/professional.json", "source_id": "prof-construction-attorney", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "bde7305204c3d006173f164e4a442b3f89e8170cc199c58ab4fd1f991a3cfb89", "role_sha256": "2b70551bbb845ed2da9288af10ffafe2a4c3f6eb253e86fb205400e36dd1dfef", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "fetch", "searxng" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-construction-estimator", "name": "Construction Estimator", "description": "Builds auditable estimates from quantities, production assumptions and market evidence", "category": "construction", "category_name": "Construction", "family": "built-environment", "family_name": "Built environment", "adaptation_state": "described", "tasks": [ "Builds auditable estimates from quantities, production assumptions and market evidence" ], "methods": [ "Planning, coordination and evidence review" ], "outputs": [ "Plans, estimates and completion records" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "matplotlib", "numpy", "openpyxl", "pandas", "pandoc", "pdfplumber", "poppler-utils", "python-docx", "scipy", "tesseract-ocr" ], "required_skills": [ "skill-construction-estimating", "skill-pdf-extraction", "skill-data-analysis" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-construction-estimator/professional.json", "source_id": "prof-construction-estimator", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "8d05a9fd9bc110852b366d649487f0e8fb0554f817cedf4d902ddb7613f3a4ef", "role_sha256": "b8458e1278b197d772b67cbf277165dcf9ea67057ececbed9971d7165a927685", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-construction-project-manager", "name": "Construction Project Manager", "description": "Controls scope, programme, cost, contracts, risk and delivery across a construction project", "category": "construction", "category_name": "Construction", "family": "built-environment", "family_name": "Built environment", "adaptation_state": "described", "tasks": [ "Controls scope, programme, cost, contracts, risk and delivery across a construction project" ], "methods": [ "Planning, coordination and evidence review" ], "outputs": [ "Plans, estimates and completion records" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "matplotlib", "numpy", "openpyxl", "pandas", "pandoc", "pdfplumber", "python-docx", "scipy" ], "required_skills": [ "skill-project-controls", "skill-contract-administration", "skill-data-analysis", "skill-business-writing" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-construction-project-manager/professional.json", "source_id": "prof-construction-project-manager", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "b8081d2664b13d359a1782b41513717288d0df7eac5d0521fe29e175dbff775e", "role_sha256": "6bf9e2b28b9439c242d4b83db35ad4594f9d8614d991e8f76a668d8499f3a230", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-construction-safety-manager", "name": "Construction Safety Manager", "description": "Manages construction hazards, controls, permits, inspections and incident learning", "category": "safety", "category_name": "Health, safety and environment", "family": "manufacturing", "family_name": "Manufacturing", "adaptation_state": "described", "tasks": [ "Manages construction hazards, controls, permits, inspections and incident learning" ], "methods": [ "Hazard assessment and control review" ], "outputs": [ "Risk register and control plan" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "openpyxl", "pandas", "pandoc", "python-docx" ], "required_skills": [ "skill-ehs-management", "skill-project-controls", "skill-business-writing" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-construction-safety-manager/professional.json", "source_id": "prof-construction-safety-manager", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "167b50e6b52e0fdd58aafc0403c464797f2a4e8f008315327aa3b58341fbdeef", "role_sha256": "4d6c2a68dc81cb9f57a466a1c581407fb25b8eac2bf8d1710ab4caca6fb66480", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-content-creator", "name": "Content Creator", "description": "Creates articles and posts, considering search discovery and social channels.", "category": "content", "category_name": "Content", "family": "research-media", "family_name": "Research and media", "adaptation_state": "described", "tasks": [ "Creates articles and posts, considering search discovery and social channels." ], "methods": [ "Source review and editorial iteration" ], "outputs": [ "Reviewable publication draft" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "beautifulsoup4", "crawl4ai", "trafilatura" ], "required_skills": [ "skill-content-writing", "skill-web-research" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-content-creator/professional.json", "source_id": "prof-content-creator", "source_version": "1.4.1", "source_lifecycle": "published", "manifest_sha256": "e10e11a4bb05012fef7747d2c663b05017e347d8be201798a6f9b311a85220e9", "role_sha256": "35462637913bb2f0b9d2ecbc66273c3264cdc2163acc8902614395244b3c7f31", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem" ], "optional": [] } }, "related_scenarios": [ "serial-content", "content-business-loop" ] }, { "id": "prof-continuous-improvement-manager", "name": "Continuous Improvement Manager", "description": "Leads evidence-based process improvement without confusing activity with realised benefit", "category": "operations", "category_name": "Operations", "family": "business", "family_name": "Business operations", "adaptation_state": "described", "tasks": [ "Leads evidence-based process improvement without confusing activity with realised benefit" ], "methods": [ "Process mapping and exception review" ], "outputs": [ "Operating plan and obligation register" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "matplotlib", "numpy", "openpyxl", "pandas", "pandoc", "python-docx", "scipy" ], "required_skills": [ "skill-manufacturing-process", "skill-quality-management", "skill-data-analysis", "skill-project-controls" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-continuous-improvement-manager/professional.json", "source_id": "prof-continuous-improvement-manager", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "773f3473c55b5e44d399f4124c221d0a26e399a8d0caf9f43c305b6d85ba3fb2", "role_sha256": "c9b6af4ac498954e9861736294c2a6ee72c4c1c42e16cc84ba22dd9d091bbd36", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-contract-manager", "name": "Commercial Contract Manager", "description": "Controls contract obligations, notices, changes, performance, claims and close-out", "category": "procurement", "category_name": "Procurement", "family": "supply-chain", "family_name": "Supply chains", "adaptation_state": "described", "tasks": [ "Controls contract obligations, notices, changes, performance, claims and close-out" ], "methods": [ "Supplier comparison and obligation review" ], "outputs": [ "Sourcing recommendation with evidence" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "openpyxl", "pandas", "pandoc", "pdfplumber", "python-docx" ], "required_skills": [ "skill-contract-administration", "skill-contract-review", "skill-supplier-management", "skill-business-writing" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-contract-manager/professional.json", "source_id": "prof-contract-manager", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "dfd493d3213ba4dde76872e6d8c5b6c5b0cbca0f05769701850202800781f2d6", "role_sha256": "3adf83bee7d12c0c8ac5743860aeb438f0527becd4110be9b81d56cceab00565", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-copywriter", "name": "Copywriter (performance)", "description": "Conversion-focused copy: ads, landing, email, sales pages", "category": "marketing", "category_name": "Marketing", "family": "commercial", "family_name": "Commercial work", "adaptation_state": "described", "tasks": [ "Conversion-focused copy: ads, landing, email, sales pages" ], "methods": [ "Audience research and measured experiments" ], "outputs": [ "Campaign plan and results analysis" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [], "required_skills": [ "skill-content-writing" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-copywriter/professional.json", "source_id": "prof-copywriter", "source_version": "1.4.1", "source_lifecycle": "published", "manifest_sha256": "0d7d7088556edb12d99af2ac6870dd0f84bb4a0f943d58d708e9470f93d812d4", "role_sha256": "510c095ed3b8e7e8a50516d3501c922d28cd4bbc860292e0702e295ea3dfbb17", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "fetch", "notion", "google-drive" ], "optional": [] } }, "related_scenarios": [ "serial-content" ] }, { "id": "prof-corporate-counsel", "name": "Corporate Counsel (in-house, general)", "description": "Contracts, corporate housekeeping, board support, regulatory triage", "category": "legal", "category_name": "Legal materials", "family": "finance-legal", "family_name": "Finance and law", "adaptation_state": "described", "tasks": [ "Contracts, corporate housekeeping, board support, regulatory triage" ], "methods": [ "Source review, issue mapping and document preparation" ], "outputs": [ "Draft for an authorized specialist" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "beautifulsoup4", "jinja2", "lxml", "openpyxl", "pandoc", "pdfplumber", "python-docx", "requests" ], "required_skills": [ "skill-contract-review", "skill-corporate-housekeeping", "skill-legal-research" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-corporate-counsel/professional.json", "source_id": "prof-corporate-counsel", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "60c3a50759e94505c4e8cb493f5494af30796d42650c84f89695b1d5cd8de31e", "role_sha256": "6c31ba5a0fedb9b46d71b820dc6226e1cc860c3a0ae4d1ee7470ab626456ec9a", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "fetch", "searxng" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-cpo", "name": "CPO / Chief Product Officer", "description": "Product strategy, roadmap orchestration, PM org, customer-problem mastery", "category": "product", "category_name": "Product", "family": "business", "family_name": "Business operations", "adaptation_state": "described", "tasks": [ "Product strategy, roadmap orchestration, PM org, customer-problem mastery" ], "methods": [ "User research, prioritization and prototyping" ], "outputs": [ "Requirements, prototype or research findings" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "openpyxl", "pandas" ], "required_skills": [ "skill-product-strategy", "skill-product-discovery", "skill-business-analysis" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-cpo/professional.json", "source_id": "prof-cpo", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "bf378afdd0c30fb821648199ac676f0b9e44efa42bc5292312473865335ed141", "role_sha256": "b49aeaa79204dc3b502b1c00d07d56e8ed70e55748a52d936a1352485723f1a4", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-criminal-defense", "name": "Criminal Defense Attorney", "description": "Investigation phase advice, charging review, plea, trial, appeal — white-collar focus", "category": "legal", "category_name": "Legal materials", "family": "finance-legal", "family_name": "Finance and law", "adaptation_state": "described", "tasks": [ "Investigation phase advice, charging review, plea, trial, appeal — white-collar focus" ], "methods": [ "Source review, issue mapping and document preparation" ], "outputs": [ "Draft for an authorized specialist" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "beautifulsoup4", "jinja2", "lxml", "pandas", "pandoc", "pdfplumber", "poppler-utils", "python-docx", "requests" ], "required_skills": [ "skill-legal-research", "skill-pleading-drafting", "skill-discovery-ediscovery" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-criminal-defense/professional.json", "source_id": "prof-criminal-defense", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "e57b70d4f7f805713f4df118ed29d9e6699eb4fcd29cb7370e82efe8a240b8ef", "role_sha256": "893190f1e1fe274785a1c2ea6a8c573e94f1cb2b7e470dfe89db016a62e578e5", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "fetch", "searxng", "brave-search" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-crypto-grant-writer", "name": "Web3 Grant Writer", "description": "Prepares applications to Web3 funding programs and explains eligibility.", "category": "content", "category_name": "Content", "family": "research-media", "family_name": "Research and media", "adaptation_state": "described", "tasks": [ "Prepares applications to Web3 funding programs and explains eligibility." ], "methods": [ "Source review and editorial iteration" ], "outputs": [ "Reviewable publication draft" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "openpyxl", "pandoc", "python-docx" ], "required_skills": [ "skill-grant-writing", "skill-business-writing" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-crypto-grant-writer/professional.json", "source_id": "prof-crypto-grant-writer", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "cbcc3570687d34a1ead02d7a3923834dcc60dd61409a7b8814934bf1d8ad5b73", "role_sha256": "bcc08a59215bd75c4ff16915b42d65899905c2549d513c831a3ef6667efc56b9", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-crypto-regulatory-analyst", "name": "Crypto Regulatory Analyst (MiCA, AML, licensing perimeter)", "description": "Maps what the organisation's crypto activity may and may not do under MiCA, AML directives and national rules: licensing perimeter, venue and stablecoin constraints, reporting duties and change monitoring; advisory, works with counsel", "category": "compliance", "category_name": "Compliance", "family": "finance-legal", "family_name": "Finance and law", "adaptation_state": "described", "tasks": [ "Maps what the organisation's crypto activity may and may not do under MiCA, AML directives and national rules: licensing perimeter, venue and stablecoin constraints, reporting duties and change monitoring; advisory, works with counsel" ], "methods": [ "Requirements mapping and control assessment" ], "outputs": [ "Requirements register and assessment" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "pandas", "pdfplumber", "python-docx" ], "required_skills": [ "skill-legal-research", "skill-sanctions-screening", "skill-business-writing", "skill-gdpr-policy" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-crypto-regulatory-analyst/professional.json", "source_id": "prof-crypto-regulatory-analyst", "source_version": "1.0.0", "source_lifecycle": "published", "manifest_sha256": "e08071e2a04ba68d836401074220e136b96332a0843d7daea69f357673d82b9e", "role_sha256": "fe10652e855efcce542abdd8142a550c4ee16530b3583ab9ec402814f8d20c28", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "fetch", "searxng" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-customer-success", "name": "Customer Success Manager", "description": "Onboarding, adoption, retention, QBR, upsell — proactive (not support)", "category": "support", "category_name": "Support", "family": "people-service", "family_name": "People and service", "adaptation_state": "described", "tasks": [ "Onboarding, adoption, retention, QBR, upsell — proactive (not support)" ], "methods": [ "Request triage, resolution checks and escalation" ], "outputs": [ "Resolved request or explicit handover" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "@google-cloud/local-auth", "google-auth", "google-auth-oauthlib", "googleapis", "openpyxl", "pandas", "pandoc", "python-docx" ], "required_skills": [ "skill-customer-success", "skill-email-triage", "skill-business-writing" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-customer-success/professional.json", "source_id": "prof-customer-success", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "6259facb4dc1c37c00cae2c8beb406210dfe18031dba2db7360b2b4377e68511", "role_sha256": "00e84d0c2aba24b73fd6c9e7dead4051139bc1ef8da3402d576927a26db0bb1b", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "fetch", "slack", "linear", "notion" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-customer-support", "name": "Customer Support (tier 1)", "description": "Ticket triage, FAQ, refunds within policy, escalation", "category": "support", "category_name": "Support", "family": "people-service", "family_name": "People and service", "adaptation_state": "described", "tasks": [ "Ticket triage, FAQ, refunds within policy, escalation" ], "methods": [ "Request triage, resolution checks and escalation" ], "outputs": [ "Resolved request or explicit handover" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "@google-cloud/local-auth", "google-auth", "google-auth-oauthlib", "googleapis" ], "required_skills": [ "skill-email-triage", "skill-content-writing" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-customer-support/professional.json", "source_id": "prof-customer-support", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "70981fb0e778d1c277c2fca686518af5c96b2a155845fbe829a531e96a7e2438", "role_sha256": "f58c1b7abaad65b831a539beacdfa099feaed2039a6981f4b93870848cb73888", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "fetch", "slack", "gmail", "notion", "linear" ], "optional": [] } }, "related_scenarios": [ "support-department-transfer", "support-service" ] }, { "id": "prof-cybercrime-forensic-analyst", "name": "Cybercrime Forensic Analyst", "description": "Cyber-fraud and scam investigations: correspondence analysis, account/domain/payment tracing, scam typology, victim manipulation patterns, OSINT correlation and evidence-backed reports", "category": "security", "category_name": "Defensive security", "family": "cyber-risk", "family_name": "Cyber risk", "adaptation_state": "described", "tasks": [ "Cyber-fraud and scam investigations: correspondence analysis, account/domain/payment tracing, scam typology, victim manipulation patterns, OSINT correlation and evidence-backed reports" ], "methods": [ "Authorized assessment and evidence review" ], "outputs": [ "Defensive findings and remediation plan" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "beautifulsoup4", "crawl4ai", "dnsutils", "git", "netcat-openbsd", "nmap", "semgrep", "trafilatura", "whois" ], "required_skills": [ "skill-security-audit", "skill-osint", "skill-web-research" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-cybercrime-forensic-analyst/professional.json", "source_id": "prof-cybercrime-forensic-analyst", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "e97f58759e831212cb7112ec26a36534993d9ee23971a687ba43248ad6f1ade6", "role_sha256": "b307810961691d731a83148a644e61f6aebb79db378c0c42048a5c6bb4c4115a", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-data-analyst", "name": "Data Analyst (BI)", "description": "SQL + dashboards + ad-hoc analysis + stakeholder reports — analyst, not modeler", "category": "data", "category_name": "Data", "family": "data-ai", "family_name": "Data and AI", "adaptation_state": "described", "tasks": [ "SQL + dashboards + ad-hoc analysis + stakeholder reports — analyst, not modeler" ], "methods": [ "Data quality checks and reproducible analysis" ], "outputs": [ "Dataset, analysis or model with checks" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "datasette", "duckdb", "ibis-framework", "matplotlib", "numpy", "pandas", "plotly", "polars", "postgresql-client", "scipy", "seaborn", "sqlite3", "streamlit" ], "required_skills": [ "skill-bi-dashboards", "skill-data-analysis" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-data-analyst/professional.json", "source_id": "prof-data-analyst", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "cf09d81506f06b2fae186674f7c2d0284a729c4677e633206dcfbe2b27a7a9c1", "role_sha256": "36686d342b741b52f4d2af115a6a41b97a464c9d5ff97d74ff94c3bb8ddce221", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "postgres", "sqlite", "fetch" ], "optional": [] } }, "related_scenarios": [ "reporting-operation", "analyst-function-transfer", "public-monitor" ] }, { "id": "prof-data-engineer", "name": "Data Engineer (pipelines, warehouses, data quality)", "description": "Builds and operates the organisation's data pipelines and warehouse: ingestion from systems and services, transformation with tests, lineage, quality checks and reliable delivery to analysts, dashboards and models", "category": "data", "category_name": "Data", "family": "data-ai", "family_name": "Data and AI", "adaptation_state": "described", "tasks": [ "Builds and operates the organisation's data pipelines and warehouse: ingestion from systems and services, transformation with tests, lineage, quality checks and reliable delivery to analysts, dashboards and models" ], "methods": [ "Data quality checks and reproducible analysis" ], "outputs": [ "Dataset, analysis or model with checks" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "dbt-core", "duckdb", "great-expectations", "pandas", "polars", "prefect", "pyarrow", "sqlalchemy" ], "required_skills": [ "skill-backend-services", "skill-data-analysis", "skill-sysadmin", "skill-test-automation" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-data-engineer/professional.json", "source_id": "prof-data-engineer", "source_version": "1.0.0", "source_lifecycle": "published", "manifest_sha256": "d2e84b144b03a33e0fbc44d0f77527f457f5c51c741b9823ff352bbf007de56b", "role_sha256": "e7ae8187805987e3a189751af8d5dac88e91a0947e7309680aa255742ddf0a65", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "fetch", "sqlite", "postgres" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-data-privacy-attorney", "name": "Data Privacy / Tech Attorney", "description": "GDPR, AI Act, e-Privacy, DSA/DMA, sector-specific (HIPAA, FCRA, COPPA)", "category": "legal", "category_name": "Legal materials", "family": "finance-legal", "family_name": "Finance and law", "adaptation_state": "described", "tasks": [ "GDPR, AI Act, e-Privacy, DSA/DMA, sector-specific (HIPAA, FCRA, COPPA)" ], "methods": [ "Source review, issue mapping and document preparation" ], "outputs": [ "Draft for an authorized specialist" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "beautifulsoup4", "jinja2", "lxml", "pandas", "pandoc", "pdfplumber", "python-docx", "requests" ], "required_skills": [ "skill-gdpr-policy", "skill-dpia", "skill-contract-review", "skill-legal-research" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-data-privacy-attorney/professional.json", "source_id": "prof-data-privacy-attorney", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "0595865f68228036bcf1c593bc5c8b21a9af17dc2dd62ebfc4e0f88427a58176", "role_sha256": "20015d5c9f5ef160b13faa22572d239d470a3a7a3f62a94f093d0603c59000bf", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "fetch", "searxng" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-data-scientist", "name": "Data Scientist", "description": "EDA, statistical analysis, hypothesis testing, viz", "category": "data", "category_name": "Data", "family": "data-ai", "family_name": "Data and AI", "adaptation_state": "described", "tasks": [ "EDA, statistical analysis, hypothesis testing, viz" ], "methods": [ "Data quality checks and reproducible analysis" ], "outputs": [ "Dataset, analysis or model with checks" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "beautifulsoup4", "build-essential", "crawl4ai", "libopenblas-dev", "lightgbm", "matplotlib", "mlflow", "numpy", "optuna", "pandas", "scikit-learn", "scipy", "statsmodels", "torch", "trafilatura", "xgboost" ], "required_skills": [ "skill-data-analysis", "skill-ml-modeling", "skill-web-research" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-data-scientist/professional.json", "source_id": "prof-data-scientist", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "1579b5f0632453466f95aa1dabebcf8663054beb448cd19cbd44a510a41d4e1f", "role_sha256": "bbc642fbfe5a16f6f8fcb4ec6f24f7b261fe65708926d5fa3ef3a2def95e0d25", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "postgres", "sqlite", "fetch" ], "optional": [] } }, "related_scenarios": [ "open-research-lab" ] }, { "id": "prof-database-admin", "name": "Database Administrator (DBA)", "description": "PostgreSQL / MySQL / Oracle / MS-SQL — tuning, backup, replication, schema migrations", "category": "engineering", "category_name": "Software engineering", "family": "technology", "family_name": "Technology", "adaptation_state": "described", "tasks": [ "PostgreSQL / MySQL / Oracle / MS-SQL — tuning, backup, replication, schema migrations" ], "methods": [ "Requirements, implementation and testing" ], "outputs": [ "Software change with test evidence" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "curl", "git", "jq", "postgresql-client", "psycopg", "sqlite3" ], "required_skills": [ "skill-database-administration", "skill-linux-sysadmin", "skill-monitoring-observability" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-database-admin/professional.json", "source_id": "prof-database-admin", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "8cd66541e63f11b4764333d88dd81071bf06f0ab86c96da67e2faa42c4f02697", "role_sha256": "bebab795ff8c14182d0a4b3080c43d6291017064dde027f2a719f655d1045581", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "postgres", "sqlite", "fetch" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-demand-planner", "name": "Demand Planner", "description": "Produces a measured consensus demand plan with bias, uncertainty and exceptions", "category": "supply-chain", "category_name": "Supply chains", "family": "supply-chain", "family_name": "Supply chains", "adaptation_state": "described", "tasks": [ "Produces a measured consensus demand plan with bias, uncertainty and exceptions" ], "methods": [ "Demand, inventory and supplier analysis" ], "outputs": [ "Supply plan with constraints" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "datasette", "duckdb", "ibis-framework", "matplotlib", "numpy", "openpyxl", "pandas", "plotly", "polars", "postgresql-client", "scipy", "seaborn", "sqlite3", "statsmodels", "streamlit" ], "required_skills": [ "skill-demand-supply-planning", "skill-data-analysis", "skill-bi-dashboards" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-demand-planner/professional.json", "source_id": "prof-demand-planner", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "812bb2602286c1eb7d05938c4d9ffbc9c0a61d938ac868f4dc70cfdde47de0c4", "role_sha256": "a57249cb128e86cd1c3882c9f6050a49f6c257bc5219552d0f06e733d2fd9a49", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-devops-sre", "name": "DevOps / SRE Engineer", "description": "IaC, K8s, CI/CD, monitoring, incident response", "category": "infra", "category_name": "Infrastructure", "family": "technology", "family_name": "Technology", "adaptation_state": "described", "tasks": [ "IaC, K8s, CI/CD, monitoring, incident response" ], "methods": [ "Change planning, monitoring and recovery review" ], "outputs": [ "Change plan or operational report" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "ansible-core", "aws-cdk", "borgbackup", "cdktf", "fabric", "fail2ban", "grafana-api", "jq", "kubernetes", "logrotate", "opentelemetry-api", "opentelemetry-sdk", "prometheus-client", "prometheus-node-exporter", "pulumi", "python-terraform", "pyyaml", "restic", "ufw", "unzip" ], "required_skills": [ "skill-iac", "skill-k8s", "skill-monitoring", "skill-sysadmin" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-devops-sre/professional.json", "source_id": "prof-devops-sre", "source_version": "1.4.1", "source_lifecycle": "published", "manifest_sha256": "6f35bc808527f5ca6d9c53faa7ff34f05b65552006964292ca1b72762f5266db", "role_sha256": "2d2a29a80e01d986c5b78d5d29365359ed0343ca6eae277787590676b3081373", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem" ], "optional": [] } }, "related_scenarios": [ "infrastructure-operator" ] }, { "id": "prof-digital-forensics-examiner", "name": "Digital Forensics Examiner", "description": "Forensic acquisition and review of digital evidence, metadata, chain-of-custody, device/account/cloud evidence handling, evidence register and court/police-ready technical reporting", "category": "security", "category_name": "Defensive security", "family": "cyber-risk", "family_name": "Cyber risk", "adaptation_state": "described", "tasks": [ "Forensic acquisition and review of digital evidence, metadata, chain-of-custody, device/account/cloud evidence handling, evidence register and court/police-ready technical reporting" ], "methods": [ "Authorized assessment and evidence review" ], "outputs": [ "Defensive findings and remediation plan" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "beautifulsoup4", "crawl4ai", "dnsutils", "git", "netcat-openbsd", "nmap", "semgrep", "trafilatura", "whois" ], "required_skills": [ "skill-security-audit", "skill-osint", "skill-web-research" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-digital-forensics-examiner/professional.json", "source_id": "prof-digital-forensics-examiner", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "fcfdfd7bc35e92102bf7a792ab8c1d192632ff2f06b82270b1287bb7c696bc96", "role_sha256": "33abfddbf8827feaef037a7106646c13e1e5084c30bce1c6c2cbd390921a3f4c", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-dpo", "name": "Data Protection Officer (DPO)", "description": "GDPR Art. 37-39 mandated role: privacy policy, RoPA, DPIA, breach response, DPA liaison", "category": "compliance", "category_name": "Compliance", "family": "cyber-risk", "family_name": "Cyber risk", "adaptation_state": "described", "tasks": [ "GDPR Art. 37-39 mandated role: privacy policy, RoPA, DPIA, breach response, DPA liaison" ], "methods": [ "Requirements mapping and control assessment" ], "outputs": [ "Requirements register and assessment" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "jinja2", "pandas", "pandoc", "pdfplumber", "python-docx" ], "required_skills": [ "skill-gdpr-policy", "skill-dpia", "skill-breach-response", "skill-contract-review" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-dpo/professional.json", "source_id": "prof-dpo", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "78a0f352c804e82d2356b2f5550790479a57f6ebee6c9fe5e79bfe3793eea1a2", "role_sha256": "ba27bf40fff73a76beea358774ab23374f8a9c04bbb02b1d981940081003108a", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "fetch", "searxng", "brave-search" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-ehs-specialist", "name": "EHS Specialist", "description": "Manages workplace health, safety and environmental risks, evidence and improvement", "category": "safety", "category_name": "Health, safety and environment", "family": "manufacturing", "family_name": "Manufacturing", "adaptation_state": "described", "tasks": [ "Manages workplace health, safety and environmental risks, evidence and improvement" ], "methods": [ "Hazard assessment and control review" ], "outputs": [ "Risk register and control plan" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "duckdb", "matplotlib", "numpy", "openpyxl", "pandas", "pandoc", "python-docx", "scipy" ], "required_skills": [ "skill-ehs-management", "skill-internal-controls", "skill-data-analysis" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-ehs-specialist/professional.json", "source_id": "prof-ehs-specialist", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "291acdcf41b12c68e35a9e779a16e7efa5833a1031f708e2befd5a2bdfa40f26", "role_sha256": "978485e37e02c403d832e3bc47782012e795ad6d6b3dfd19d731cc443e78a1c9", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-email-marketer", "name": "Email Marketer / Lifecycle / CRM", "description": "Lifecycle automation, segmentation, deliverability, A/B testing", "category": "marketing", "category_name": "Marketing", "family": "commercial", "family_name": "Commercial work", "adaptation_state": "described", "tasks": [ "Lifecycle automation, segmentation, deliverability, A/B testing" ], "methods": [ "Audience research and measured experiments" ], "outputs": [ "Campaign plan and results analysis" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [], "required_skills": [ "skill-content-writing" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-email-marketer/professional.json", "source_id": "prof-email-marketer", "source_version": "1.4.1", "source_lifecycle": "published", "manifest_sha256": "d706f40a19f8d13f40306e0518969dcf64caa6c42f4bee055ddc64b69cd3b1a6", "role_sha256": "7e5f160aae341aa34c48b24e4e4d1c589af2576c21779a98d53856d2f2fce979", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "fetch", "gmail" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-embedded-engineer", "name": "Embedded / Firmware Engineer", "description": "C/C++/Rust on MCUs, RTOS, IoT, hardware-software boundary", "category": "engineering", "category_name": "Software engineering", "family": "technology", "family_name": "Technology", "adaptation_state": "described", "tasks": [ "C/C++/Rust on MCUs, RTOS, IoT, hardware-software boundary" ], "methods": [ "Requirements, implementation and testing" ], "outputs": [ "Software change with test evidence" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "@playwright/test", "cypress", "faker", "gcc-arm-none-eabi", "gdb-multiarch", "git", "hypothesis", "pyserial", "pytest", "pytest-asyncio", "pytest-xdist", "vitest" ], "required_skills": [ "skill-embedded-systems", "skill-code-review", "skill-test-automation" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-embedded-engineer/professional.json", "source_id": "prof-embedded-engineer", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "24b6544c99b1a2c5711cef4bbf2f10742d157c6c08f54e406279521198ba272e", "role_sha256": "16353ae8dfe6be07b3c19e622e49475efeeb986bf3963ac636a8f6c23e75bf96", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "github", "fetch" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-employment-attorney", "name": "Employment / Labor Attorney", "description": "Hiring, contracts, dismissal, discrimination, works council, collective bargaining", "category": "legal", "category_name": "Legal materials", "family": "finance-legal", "family_name": "Finance and law", "adaptation_state": "described", "tasks": [ "Hiring, contracts, dismissal, discrimination, works council, collective bargaining" ], "methods": [ "Source review, issue mapping and document preparation" ], "outputs": [ "Draft for an authorized specialist" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "beautifulsoup4", "jinja2", "lxml", "pandoc", "pdfplumber", "python-docx", "requests" ], "required_skills": [ "skill-contract-review", "skill-legal-research", "skill-pleading-drafting" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-employment-attorney/professional.json", "source_id": "prof-employment-attorney", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "1fb8031e2a592a310b45fa23d6b3bc2740f3020559c1b8293451aafb47f54f44", "role_sha256": "d41221f50ace8a1f85bc631033775fa9f30c76dd1b6635990c5556c6c4977448", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "fetch", "searxng" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-execution-engineer", "name": "Execution Engineer (algorithmic trading systems, venue connectivity, pre-trade controls)", "description": "Builds and operates the systems that turn validated signals into orders: venue connectors, order management, pre-trade risk filters, kill switches and reconciliation; owns latency, correctness and safety of execution", "category": "engineering", "category_name": "Software engineering", "family": "technology", "family_name": "Technology", "adaptation_state": "described", "tasks": [ "Builds and operates the systems that turn validated signals into orders: venue connectors, order management, pre-trade risk filters, kill switches and reconciliation; owns latency, correctness and safety of execution" ], "methods": [ "Requirements, implementation and testing" ], "outputs": [ "Software change with test evidence" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "aiohttp", "ccxt", "duckdb", "numpy", "pandas", "pydantic", "pytest", "websockets" ], "required_skills": [ "skill-backend-services", "skill-test-automation", "skill-financial-systems" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-execution-engineer/professional.json", "source_id": "prof-execution-engineer", "source_version": "1.0.0", "source_lifecycle": "published", "manifest_sha256": "bd6e5da8d8f899ba37c8c102d9de2651a023bb5eefd21fc92dae8be475cd81c5", "role_sha256": "52dc1e3371309f43b0e341e843d6b45c552e0ac3c1a4bc526bf38424d60a12d9", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "fetch", "github", "sqlite" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-facilities-manager", "name": "Facilities Manager", "description": "Controls building assets, maintenance, compliance, space, vendors and service continuity", "category": "facilities", "category_name": "Facilities and property", "family": "built-environment", "family_name": "Built environment", "adaptation_state": "described", "tasks": [ "Controls building assets, maintenance, compliance, space, vendors and service continuity" ], "methods": [ "Asset registers and service planning" ], "outputs": [ "Maintenance or occupancy plan" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "openpyxl", "pandas", "pandoc", "python-docx" ], "required_skills": [ "skill-facilities-management", "skill-supplier-management", "skill-project-controls" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-facilities-manager/professional.json", "source_id": "prof-facilities-manager", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "2e542a6ca405bfcc05a63d4fae5e757c62001cfdb3c48ea5caa73e54edf01331", "role_sha256": "07126f0984d8fc44756412fae118718a993d2db55eb3bb263628f2cca27009a4", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-family-law-attorney", "name": "Family Law Attorney", "description": "Divorce, custody, support, prenup, adoption, domestic violence", "category": "legal", "category_name": "Legal materials", "family": "finance-legal", "family_name": "Finance and law", "adaptation_state": "described", "tasks": [ "Divorce, custody, support, prenup, adoption, domestic violence" ], "methods": [ "Source review, issue mapping and document preparation" ], "outputs": [ "Draft for an authorized specialist" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "beautifulsoup4", "jinja2", "lxml", "pandoc", "python-docx", "requests" ], "required_skills": [ "skill-legal-research", "skill-pleading-drafting" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-family-law-attorney/professional.json", "source_id": "prof-family-law-attorney", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "e8ce09f7670d28beab491e48ddc5a0bdb0ca28c3f6c4a1ab326dd5cea9006042", "role_sha256": "f15ff05fb6a3e6d0e4e6884828b1694b3d3c87319930f2c8f4649c1d50c720c1", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "fetch", "searxng" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-financial-advisor", "name": "Financial Advisor / Wealth Manager", "description": "Personal finance: retirement, tax-efficient investing, estate basics", "category": "finance", "category_name": "Finance", "family": "finance-legal", "family_name": "Finance and law", "adaptation_state": "described", "tasks": [ "Personal finance: retirement, tax-efficient investing, estate basics" ], "methods": [ "Reconciliation, scenario analysis and limit review" ], "outputs": [ "Financial model or report with assumptions" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "numpy", "numpy-financial", "openpyxl", "pandas", "pandoc", "python-docx" ], "required_skills": [ "skill-financial-advice", "skill-risk-analysis", "skill-business-writing" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-financial-advisor/professional.json", "source_id": "prof-financial-advisor", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "b1b3d4d051aa14da1c0e5a4b1e4c5719b4dfff9f271c7fb173bf281d82b8c661", "role_sha256": "3f8d5e8a8119ecdffa36ea7e4d3f267f65956faf2352c6dd710cd73971f5af33", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "fetch", "searxng", "sqlite" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-fpa-analyst", "name": "FP&A Analyst", "description": "Budgeting, forecasting, variance, models, dashboards", "category": "finance", "category_name": "Finance", "family": "finance-legal", "family_name": "Finance and law", "adaptation_state": "described", "tasks": [ "Budgeting, forecasting, variance, models, dashboards" ], "methods": [ "Reconciliation, scenario analysis and limit review" ], "outputs": [ "Financial model or report with assumptions" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "arelle-release", "datasette", "duckdb", "fixparser", "ibis-framework", "matplotlib", "pandas", "plotly", "polars", "postgresql-client", "pycountry", "python-iso20022", "schwifty", "seaborn", "sepaxml", "sqlite3", "streamlit" ], "required_skills": [ "skill-bi-dashboards", "skill-financial-systems" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-fpa-analyst/professional.json", "source_id": "prof-fpa-analyst", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "a595ca269e932f67f29a76e9da8b4ae7d131f7215a51422ea9763646e7f0de87", "role_sha256": "2b3efe3c01ef78a6d3049c63fa3ba6441b1bff8d4a0854d22e932b37abbf7bfc", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "fetch", "sqlite", "postgres" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-fraud-investigator", "name": "Fraud Investigator", "description": "Financial and identity fraud investigation: transaction timelines, counterparties, shell identities, mule/payment indicators, loss summaries and recovery/escalation packets", "category": "security", "category_name": "Defensive security", "family": "cyber-risk", "family_name": "Cyber risk", "adaptation_state": "described", "tasks": [ "Financial and identity fraud investigation: transaction timelines, counterparties, shell identities, mule/payment indicators, loss summaries and recovery/escalation packets" ], "methods": [ "Authorized assessment and evidence review" ], "outputs": [ "Defensive findings and remediation plan" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "beautifulsoup4", "crawl4ai", "dnsutils", "matplotlib", "netcat-openbsd", "nmap", "numpy", "pandas", "scipy", "trafilatura", "whois" ], "required_skills": [ "skill-osint", "skill-web-research", "skill-data-analysis" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-fraud-investigator/professional.json", "source_id": "prof-fraud-investigator", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "ef426a14cfd1f2556bfd583790cda2824e9c59f73f688979e002b264913b8253", "role_sha256": "cd18412d4dea455700922f44904e52bd85fe80ae3f57ff30c0a93ea1b5546488", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-frontend-engineer", "name": "Frontend Engineer", "description": "React / Vue / Svelte SPA, a11y, Core Web Vitals, design systems", "category": "engineering", "category_name": "Software engineering", "family": "technology", "family_name": "Technology", "adaptation_state": "described", "tasks": [ "React / Vue / Svelte SPA, a11y, Core Web Vitals, design systems" ], "methods": [ "Requirements, implementation and testing" ], "outputs": [ "Software change with test evidence" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "@playwright/test", "create-next-app", "cypress", "eslint", "faker", "hypothesis", "prettier", "pytest", "pytest-asyncio", "pytest-xdist", "typescript", "vite", "vitest" ], "required_skills": [ "skill-frontend-modern", "skill-test-automation" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-frontend-engineer/professional.json", "source_id": "prof-frontend-engineer", "source_version": "1.4.1", "source_lifecycle": "published", "manifest_sha256": "487038a0d36ea93a15d1e0691db9fa8ab301f982785f6c5574ff863c0ab7dd0e", "role_sha256": "80bbea26644d99c92b37d183fc5fe3c628c7066fe5eff9ccab490a14cd5132aa", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "github", "fetch", "puppeteer" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-fullstack", "name": "Full-stack Engineer", "description": "Modern frontend + backend, TypeScript end-to-end", "category": "engineering", "category_name": "Software engineering", "family": "technology", "family_name": "Technology", "adaptation_state": "described", "tasks": [ "Modern frontend + backend, TypeScript end-to-end" ], "methods": [ "Requirements, implementation and testing" ], "outputs": [ "Software change with test evidence" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "alembic", "asyncpg", "celery", "create-next-app", "eslint", "fastapi", "httpx", "postgresql-client", "prettier", "pydantic", "redis", "redis-tools", "sqlalchemy", "typescript", "uvicorn", "vite" ], "required_skills": [ "skill-frontend-modern", "skill-backend-services" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-fullstack/professional.json", "source_id": "prof-fullstack", "source_version": "1.5.2", "source_lifecycle": "published", "manifest_sha256": "05d46845b6e28a69b1c8449c652512569ed75abd29dc2cdcd48f4e141202b7b9", "role_sha256": "3bea8ea017d53c70b12b7f3030f2f43c293cb473f2172ddf7c7cda9935f53c6f", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem" ], "optional": [] } }, "related_scenarios": [ "software-service" ] }, { "id": "prof-fund-administrator", "name": "Fund Administrator (NAV, investor accounting, statements)", "description": "Keeps the fund's books of record: NAV calculation, capital accounts per investor, fees and expenses, reconciliations with venues and custody, and periodic statements; independent of trading decisions", "category": "finance", "category_name": "Finance", "family": "finance-legal", "family_name": "Finance and law", "adaptation_state": "described", "tasks": [ "Keeps the fund's books of record: NAV calculation, capital accounts per investor, fees and expenses, reconciliations with venues and custody, and periodic statements; independent of trading decisions" ], "methods": [ "Reconciliation, scenario analysis and limit review" ], "outputs": [ "Financial model or report with assumptions" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "ccxt", "duckdb", "openpyxl", "pandas", "python-dateutil" ], "required_skills": [ "skill-bookkeeping", "skill-financial-systems", "skill-internal-controls", "skill-data-analysis" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-fund-administrator/professional.json", "source_id": "prof-fund-administrator", "source_version": "1.0.0", "source_lifecycle": "published", "manifest_sha256": "463fdc4047317e4bb05628bc775d24214a0c7dcc68a05b92437ccf52a95960c4", "role_sha256": "1f8b7207e45664367dbd278bc585ec8e3a64854e78465c8f35078b6fd72d8d0b", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "fetch", "sqlite" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-gamedev", "name": "Game Developer", "description": "Godot/Unity logic, GDScript/C#, asset pipelines", "category": "engineering", "category_name": "Software engineering", "family": "technology", "family_name": "Technology", "adaptation_state": "described", "tasks": [ "Godot/Unity logic, GDScript/C#, asset pipelines" ], "methods": [ "Requirements, implementation and testing" ], "outputs": [ "Software change with test evidence" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "blender", "create-next-app", "eslint", "ffmpeg", "git-lfs", "imagemagick", "matplotlib", "numpy", "panda3d", "pandas", "pillow", "prettier", "pygame", "scipy", "typescript", "vite" ], "required_skills": [ "skill-gamedev", "skill-frontend-modern", "skill-data-analysis" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-gamedev/professional.json", "source_id": "prof-gamedev", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "7fec357a3684825e31aad89a55957f8c6b7807d443061ff857e8bf7f3cf08350", "role_sha256": "cdcba6949eec4caa4ce56bdfe8b7470f2ad691c01082d0ddeea17f7941750f12", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem" ], "optional": [] } }, "related_scenarios": [ "game-project" ] }, { "id": "prof-graphic-designer", "name": "Graphic Designer (brand identity, visual systems, marketing and product visuals)", "description": "Creates the organisation's visual identity and applies it consistently: logo and brand system, typography and colour, templates, marketing and product visuals, presentation and document design; briefs generation tools and keeps quality and licensing in order", "category": "marketing", "category_name": "Marketing", "family": "research-media", "family_name": "Research and media", "adaptation_state": "described", "tasks": [ "Creates the organisation's visual identity and applies it consistently: logo and brand system, typography and colour, templates, marketing and product visuals, presentation and document design; briefs generation tools and keeps quality and licensing in order" ], "methods": [ "Audience research and measured experiments" ], "outputs": [ "Campaign plan and results analysis" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "Pillow", "cairosvg", "fonts-dejavu", "fonttools", "imagemagick", "inkscape" ], "required_skills": [ "skill-content-writing", "skill-business-writing" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-graphic-designer/professional.json", "source_id": "prof-graphic-designer", "source_version": "1.0.0", "source_lifecycle": "published", "manifest_sha256": "b9feb84fd684a1b4eff73bc75108e341fbbf537dc92785b45a8682cd16f1dc91", "role_sha256": "8c02a5f31d0411590966ba3ce18c7261a67412705c26aa70e98e6e0ebeddb6c1", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "fetch", "puppeteer" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-growth-hacker", "name": "Growth Hacker", "description": "Experimentation pipeline, funnel optimization, viral loops, referrals", "category": "marketing", "category_name": "Marketing", "family": "commercial", "family_name": "Commercial work", "adaptation_state": "described", "tasks": [ "Experimentation pipeline, funnel optimization, viral loops, referrals" ], "methods": [ "Audience research and measured experiments" ], "outputs": [ "Campaign plan and results analysis" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "matplotlib", "numpy", "pandas", "scipy" ], "required_skills": [ "skill-data-analysis" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-growth-hacker/professional.json", "source_id": "prof-growth-hacker", "source_version": "1.4.1", "source_lifecycle": "published", "manifest_sha256": "83d3bc450db7f00df5bd427077db14858ca61ff6ed813b18a4c35977a5bf3e8c", "role_sha256": "fe20ce853f7303147bb20470c117a2336ec935e4df96e8aafee3f46feaadaee0", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "fetch", "postgres", "sqlite", "notion" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-hipaa-officer", "name": "HIPAA Privacy / Security Officer", "description": "HIPAA Privacy + Security + Breach Notification compliance for healthcare", "category": "compliance", "category_name": "Compliance", "family": "cyber-risk", "family_name": "Cyber risk", "adaptation_state": "described", "tasks": [ "HIPAA Privacy + Security + Breach Notification compliance for healthcare" ], "methods": [ "Requirements mapping and control assessment" ], "outputs": [ "Requirements register and assessment" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "duckdb", "openpyxl", "pandas", "pandoc", "pdfplumber", "python-docx" ], "required_skills": [ "skill-gdpr-policy", "skill-internal-controls" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-hipaa-officer/professional.json", "source_id": "prof-hipaa-officer", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "246a860e4f6d02c811568e9239385bc482059f24924f4d8a0e802d21adb32a3f", "role_sha256": "09aa89a101097e180c05be86193fcde72cf5bc5ff787ef9e433bfea26784df33", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "fetch" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-hr-payroll", "name": "HR / Payroll Specialist", "description": "Hiring docs, contracts, payroll, leave, terminations per local labor law", "category": "hr", "category_name": "People and learning", "family": "people-service", "family_name": "People and service", "adaptation_state": "described", "tasks": [ "Hiring docs, contracts, payroll, leave, terminations per local labor law" ], "methods": [ "Needs assessment and structured documentation" ], "outputs": [ "Reviewed personnel or learning materials" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "openpyxl", "pandas", "pandoc", "pdfplumber", "python-dateutil", "python-docx" ], "required_skills": [ "skill-payroll", "skill-contract-review", "skill-gdpr-policy" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-hr-payroll/professional.json", "source_id": "prof-hr-payroll", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "94cb251e1d98e1c2e281bae96b73bfe1a513d08f6298934acd9f5d7e3e22f599", "role_sha256": "7283e1699844038dbc373c70e937bb7d7b26be16f8605ad7d91f62d9c1dfadc8", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "fetch", "slack", "gmail", "google-drive" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-immigration-attorney", "name": "Immigration Attorney", "description": "Visas, work permits, asylum, naturalization, removal defense", "category": "legal", "category_name": "Legal materials", "family": "finance-legal", "family_name": "Finance and law", "adaptation_state": "described", "tasks": [ "Visas, work permits, asylum, naturalization, removal defense" ], "methods": [ "Source review, issue mapping and document preparation" ], "outputs": [ "Draft for an authorized specialist" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "beautifulsoup4", "lxml", "pandoc", "requests" ], "required_skills": [ "skill-legal-research" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-immigration-attorney/professional.json", "source_id": "prof-immigration-attorney", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "bf45e6f774febee4006f83544cba08c1536c81ebdb6ed52dffcb0b160ad02708", "role_sha256": "50c2b4fd55602800fc9a322a8ac39d394962f413ee61d5017595f454cc2fe5ec", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "fetch", "searxng" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-incident-response-analyst", "name": "Incident Response Analyst", "description": "Security incident triage and response: scope assessment, containment plan, IOC collection, log/evidence review, attacker timeline, remediation and post-incident report", "category": "security", "category_name": "Defensive security", "family": "cyber-risk", "family_name": "Cyber risk", "adaptation_state": "described", "tasks": [ "Security incident triage and response: scope assessment, containment plan, IOC collection, log/evidence review, attacker timeline, remediation and post-incident report" ], "methods": [ "Authorized assessment and evidence review" ], "outputs": [ "Defensive findings and remediation plan" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "ansible-core", "borgbackup", "dnsutils", "fabric", "fail2ban", "git", "httpx", "logrotate", "mitmproxy", "netcat-openbsd", "nikto", "nmap", "prometheus-node-exporter", "requests", "restic", "semgrep", "sqlmap", "ufw", "wfuzz", "whatweb", "whois" ], "required_skills": [ "skill-security-audit", "skill-web-security", "skill-osint", "skill-sysadmin" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-incident-response-analyst/professional.json", "source_id": "prof-incident-response-analyst", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "481124a6659eca120ce0978fe39740ec744a2abec260562f0cca055d4908f278", "role_sha256": "0f9cadb55e96bbc09c648ff968347ef09f16472e0699fe9e14bddc157a627e4d", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-industrial-engineer", "name": "Industrial Engineer", "description": "Optimises flow, capacity, layout, labour, queues and productivity using measured systems data", "category": "manufacturing", "category_name": "Manufacturing", "family": "manufacturing", "family_name": "Manufacturing", "adaptation_state": "described", "tasks": [ "Optimises flow, capacity, layout, labour, queues and productivity using measured systems data" ], "methods": [ "Capacity planning and controlled improvement" ], "outputs": [ "Feasible production plan" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "datasette", "duckdb", "ibis-framework", "matplotlib", "numpy", "openpyxl", "pandas", "plotly", "polars", "postgresql-client", "python-docx", "scipy", "seaborn", "sqlite3", "streamlit" ], "required_skills": [ "skill-manufacturing-process", "skill-data-analysis", "skill-bi-dashboards" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-industrial-engineer/professional.json", "source_id": "prof-industrial-engineer", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "a90ef9f861f6dd97f54a5ac97c441394a987f52272fbcbcbc09a62ff6878573e", "role_sha256": "7329aaea6a558b622cd126742d917ed3c357c06c70ab3e7adaafe27160b43068", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-insolvency-attorney", "name": "Insolvency / Restructuring Attorney", "description": "Bankruptcy filings, restructuring plans, creditor work-outs, cross-border insolvency", "category": "legal", "category_name": "Legal materials", "family": "finance-legal", "family_name": "Finance and law", "adaptation_state": "described", "tasks": [ "Bankruptcy filings, restructuring plans, creditor work-outs, cross-border insolvency" ], "methods": [ "Source review, issue mapping and document preparation" ], "outputs": [ "Draft for an authorized specialist" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "beautifulsoup4", "jinja2", "lxml", "pandoc", "pdfplumber", "python-docx", "requests" ], "required_skills": [ "skill-pleading-drafting", "skill-legal-research", "skill-contract-review" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-insolvency-attorney/professional.json", "source_id": "prof-insolvency-attorney", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "0a486423f78d64c274b5b307984d6cc5e593eed85c9717dff3c06e1751dabb6b", "role_sha256": "ec82ea2c4b534537a24b242f39cbb344d9d1d183014ea979791e5447b147a1f7", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "fetch" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-insurance-underwriter", "name": "Insurance Underwriter / Broker", "description": "Risk selection, pricing, policy structuring (P&C / specialty / health)", "category": "finance", "category_name": "Finance", "family": "finance-legal", "family_name": "Finance and law", "adaptation_state": "described", "tasks": [ "Risk selection, pricing, policy structuring (P&C / specialty / health)" ], "methods": [ "Reconciliation, scenario analysis and limit review" ], "outputs": [ "Financial model or report with assumptions" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "matplotlib", "numpy", "openpyxl", "pandas", "scipy" ], "required_skills": [ "skill-insurance-underwriting", "skill-risk-analysis", "skill-data-analysis" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-insurance-underwriter/professional.json", "source_id": "prof-insurance-underwriter", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "8b73c0467ea58d0553848e78033733404464c8b8ff62a43a961cde4126d962aa", "role_sha256": "d541e8b656edeaf85be128cdd5fff585d7d5c6c89e5a1418b48010364ce9ebed", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "fetch", "sqlite" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-internal-auditor", "name": "Internal Auditor", "description": "Risk-based audit plan, control testing, finding write-up, follow-up", "category": "audit", "category_name": "Audit", "family": "cyber-risk", "family_name": "Cyber risk", "adaptation_state": "described", "tasks": [ "Risk-based audit plan, control testing, finding write-up, follow-up" ], "methods": [ "Risk-based control review" ], "outputs": [ "Findings with evidence and follow-up" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "beautifulsoup4", "duckdb", "matplotlib", "numpy", "openpyxl", "pandas", "requests", "scipy" ], "required_skills": [ "skill-internal-controls", "skill-data-analysis", "skill-vendor-due-diligence" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-internal-auditor/professional.json", "source_id": "prof-internal-auditor", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "afa0eee5f5048b7e9bee0b7c717fadb597bec829b1e29a9458b10dcd7996059f", "role_sha256": "dcd216e51af27589abd515accb92d4624191db870f3b7f274de969f8513b3781", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "fetch", "sqlite" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-inventory-planner", "name": "Inventory Planner", "description": "Sets replenishment and safety-stock policies from service, variability and lead-time evidence", "category": "supply-chain", "category_name": "Supply chains", "family": "supply-chain", "family_name": "Supply chains", "adaptation_state": "described", "tasks": [ "Sets replenishment and safety-stock policies from service, variability and lead-time evidence" ], "methods": [ "Demand, inventory and supplier analysis" ], "outputs": [ "Supply plan with constraints" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "datasette", "duckdb", "ibis-framework", "matplotlib", "numpy", "openpyxl", "pandas", "plotly", "polars", "postgresql-client", "scipy", "seaborn", "sqlite3", "statsmodels", "streamlit" ], "required_skills": [ "skill-demand-supply-planning", "skill-data-analysis", "skill-bi-dashboards" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-inventory-planner/professional.json", "source_id": "prof-inventory-planner", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "d05e40339fe049a47a36884fc9f1dac60a2ba4817a7b1aecf6b44640878e2594", "role_sha256": "0fd2eefe8529203cd8c4e8e1299d92225c0b0a4aede95f773abfa359872cb24c", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-investigative-journalist", "name": "Investigative Journalist", "description": "Source verification, FOIA / RTI, document analysis, OSINT for stories", "category": "research", "category_name": "Research", "family": "research-media", "family_name": "Research and media", "adaptation_state": "described", "tasks": [ "Source verification, FOIA / RTI, document analysis, OSINT for stories" ], "methods": [ "Question framing, source evaluation and hypothesis tests" ], "outputs": [ "Report with sources and uncertainty" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "beautifulsoup4", "crawl4ai", "dnsutils", "netcat-openbsd", "nmap", "pandoc", "poppler-utils", "tesseract-ocr", "trafilatura", "whois" ], "required_skills": [ "skill-web-research", "skill-osint", "skill-pdf-extraction" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-investigative-journalist/professional.json", "source_id": "prof-investigative-journalist", "source_version": "1.4.1", "source_lifecycle": "published", "manifest_sha256": "29c8c68eacd75f8953b3c367f76cd5923c8995ca4416e313f9f23fc3e25287df", "role_sha256": "e67f59efc8bb380319609bbceb100c254e74c38f17ed5b289b0da15e6b2fed77", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "fetch", "searxng", "brave-search", "puppeteer" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-investment-analyst", "name": "Investment / M&A Analyst", "description": "Valuation (DCF / comparables), due diligence, deal modeling", "category": "finance", "category_name": "Finance", "family": "finance-legal", "family_name": "Finance and law", "adaptation_state": "described", "tasks": [ "Valuation (DCF / comparables), due diligence, deal modeling" ], "methods": [ "Reconciliation, scenario analysis and limit review" ], "outputs": [ "Financial model or report with assumptions" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "arelle-release", "datasette", "duckdb", "fixparser", "ibis-framework", "matplotlib", "pandas", "plotly", "polars", "postgresql-client", "pycountry", "python-iso20022", "schwifty", "seaborn", "sepaxml", "sqlite3", "streamlit" ], "required_skills": [ "skill-financial-systems", "skill-bi-dashboards" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-investment-analyst/professional.json", "source_id": "prof-investment-analyst", "source_version": "1.4.1", "source_lifecycle": "published", "manifest_sha256": "5da536971af83b0f262b6fae8f4ec9142add1e776193a0e90993a12c858f22a3", "role_sha256": "752a3ad8a8c9748476c02dab2a476a63f1e88dcbf1ec5b59ad952fa08d042699", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "fetch", "searxng", "sqlite" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-investor-relations-manager", "name": "Investor Relations Manager (reporting, communication, capital relationships)", "description": "Owns the relationship with investors and the owner as capital provider: periodic reports, letters, onboarding materials, questions and expectations; turns the organisation's numbers into truthful, timely communication", "category": "marketing", "category_name": "Marketing", "family": "commercial", "family_name": "Commercial work", "adaptation_state": "described", "tasks": [ "Owns the relationship with investors and the owner as capital provider: periodic reports, letters, onboarding materials, questions and expectations; turns the organisation's numbers into truthful, timely communication" ], "methods": [ "Audience research and measured experiments" ], "outputs": [ "Campaign plan and results analysis" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "matplotlib", "openpyxl", "pandas", "python-docx" ], "required_skills": [ "skill-business-writing", "skill-financial-systems", "skill-bi-dashboards" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-investor-relations-manager/professional.json", "source_id": "prof-investor-relations-manager", "source_version": "1.0.0", "source_lifecycle": "published", "manifest_sha256": "2a46437e4287e875b04c5f305da7d3b5ef9fb224ea80cd61313f239c027cf798", "role_sha256": "17f1f046db58c3b178fccae143b652fc1e7d0d1a2cf6042e0a557d6e8662c558", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "fetch" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-ios-engineer", "name": "iOS Engineer", "description": "Swift / SwiftUI, App Store, push, in-app purchases, Apple ecosystem", "category": "engineering", "category_name": "Software engineering", "family": "technology", "family_name": "Technology", "adaptation_state": "described", "tasks": [ "Swift / SwiftUI, App Store, push, in-app purchases, Apple ecosystem" ], "methods": [ "Requirements, implementation and testing" ], "outputs": [ "Software change with test evidence" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "@expo/cli", "android-tools-adb", "eas-cli", "openjdk-17-jdk", "react-native-cli" ], "required_skills": [ "skill-mobile-android" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-ios-engineer/professional.json", "source_id": "prof-ios-engineer", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "ee67d995c99f062f487b88c567bb041f787a57a66c2cf91ccec393a34efecda3", "role_sha256": "32a47ff83ee7999b62ed07a9762597ba657c72726a8c40241d11418419ebd898", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "github", "fetch" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-ip-attorney", "name": "IP Attorney (patent + trademark)", "description": "Prosecution, freedom-to-operate, infringement analysis, licensing", "category": "legal", "category_name": "Legal materials", "family": "finance-legal", "family_name": "Finance and law", "adaptation_state": "described", "tasks": [ "Prosecution, freedom-to-operate, infringement analysis, licensing" ], "methods": [ "Source review, issue mapping and document preparation" ], "outputs": [ "Draft for an authorized specialist" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "beautifulsoup4", "lxml", "pandoc", "pdfplumber", "python-docx", "requests" ], "required_skills": [ "skill-ip-prosecution", "skill-legal-research", "skill-contract-review" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-ip-attorney/professional.json", "source_id": "prof-ip-attorney", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "eaed26dea59681446aa7c4d85b02cb5cc08042b323dcc22daff725e6f570d85d", "role_sha256": "2d75b8c67986629fc2afaa8df1f81305bd29c1236e53e559d21b356632908f3b", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "fetch", "searxng", "brave-search" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-it-support-specialist", "name": "IT Support Specialist (accounts, devices, access, first-line incidents)", "description": "Keeps people and tools working: accounts and access, devices and software, first-line incident response and triage, onboarding and offboarding, security hygiene; documents fixes and escalates what is beyond first line", "category": "infra", "category_name": "Infrastructure", "family": "technology", "family_name": "Technology", "adaptation_state": "described", "tasks": [ "Keeps people and tools working: accounts and access, devices and software, first-line incident response and triage, onboarding and offboarding, security hygiene; documents fixes and escalates what is beyond first line" ], "methods": [ "Change planning, monitoring and recovery review" ], "outputs": [ "Change plan or operational report" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "pandas" ], "required_skills": [ "skill-sysadmin", "skill-email-triage", "skill-web-security" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-it-support-specialist/professional.json", "source_id": "prof-it-support-specialist", "source_version": "1.0.0", "source_lifecycle": "published", "manifest_sha256": "7ee472ad20a3ee6b21e1519eba4390d911526fd48c6f28e1a7ab0722e1ebcd07", "role_sha256": "8a0b9ca2a088c55fabd542258619a3b283f798e37f02fba0d1593908fc7b65d3", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "fetch" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-kyc-aml", "name": "KYC / AML Compliance Specialist", "description": "Customer due diligence, sanctions screening, transaction monitoring, SAR/STR filing", "category": "compliance", "category_name": "Compliance", "family": "cyber-risk", "family_name": "Cyber risk", "adaptation_state": "described", "tasks": [ "Customer due diligence, sanctions screening, transaction monitoring, SAR/STR filing" ], "methods": [ "Requirements mapping and control assessment" ], "outputs": [ "Requirements register and assessment" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "duckdb", "fuzzywuzzy", "jinja2", "lxml", "numpy", "pandas", "pandoc", "python-Levenshtein", "python-docx", "requests", "scikit-learn", "unidecode" ], "required_skills": [ "skill-kyc-cdd", "skill-sanctions-screening", "skill-transaction-monitoring", "skill-sar-drafting" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-kyc-aml/professional.json", "source_id": "prof-kyc-aml", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "f402f0ea3007e4e8ba0fa8a1f8c1e65a9e0278c318e7ae34a6f9d7a6929e78d3", "role_sha256": "a68163d678dfd70ad5f4ce5f42899f24be840fc6bab63bd2cb609acd7e9b4456", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "fetch", "searxng", "brave-search" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-land-surveyor", "name": "Land Surveyor / Geomatics Specialist", "description": "Plans and reviews geospatial control, boundary, topographic and setting-out information", "category": "architecture", "category_name": "Architecture", "family": "built-environment", "family_name": "Built environment", "adaptation_state": "described", "tasks": [ "Plans and reviews geospatial control, boundary, topographic and setting-out information" ], "methods": [ "Requirements and interface coordination" ], "outputs": [ "Coordinated design requirements" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "matplotlib", "numpy", "openpyxl", "pandas", "pandoc", "python-docx", "scipy" ], "required_skills": [ "skill-data-analysis", "skill-project-controls", "skill-business-writing" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-land-surveyor/professional.json", "source_id": "prof-land-surveyor", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "3cb8a8f62e2be1be5fe5b603e8175c76d4851505f18747e37c3b8eb095b1a223", "role_sha256": "e39656c5a8d7f1c4b9a657ec1c73ddb00bfd0135577d664300402ab32818118f", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-launchpad-allocator", "name": "Token Offering Analyst", "description": "Studies allocation across token offerings within explicit constraints.", "category": "finance", "category_name": "Finance", "family": "finance-legal", "family_name": "Finance and law", "adaptation_state": "described", "tasks": [ "Studies allocation across token offerings within explicit constraints." ], "methods": [ "Reconciliation, scenario analysis and limit review" ], "outputs": [ "Financial model or report with assumptions" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "arelle-release", "fixparser", "pycountry", "python-iso20022", "schwifty", "sepaxml" ], "required_skills": [ "skill-financial-systems" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-launchpad-allocator/professional.json", "source_id": "prof-launchpad-allocator", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "3dfc75a8e067a033af31ebe5d2cc434bfa5528b3246804b480b80b782f6ea815", "role_sha256": "13a96422e545530139c6866bfd4f5b70baf4b15e218488b8db85fc2998a3ebb4", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-learning-development", "name": "Learning & Development Specialist", "description": "Onboarding, training programs, LMS, performance management, career frameworks", "category": "hr", "category_name": "People and learning", "family": "people-service", "family_name": "People and service", "adaptation_state": "described", "tasks": [ "Onboarding, training programs, LMS, performance management, career frameworks" ], "methods": [ "Needs assessment and structured documentation" ], "outputs": [ "Reviewed personnel or learning materials" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [], "required_skills": [ "skill-content-writing" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-learning-development/professional.json", "source_id": "prof-learning-development", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "bb6028077967806673407b96486ad829615ba52a8e82946ebbe8f0e318886ea0", "role_sha256": "be74a2779b44bcd50b42b2951c575f6efff1edfb937cc52d5f89b6f519a64e1c", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "fetch", "notion" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-litigation-attorney", "name": "Litigation Attorney", "description": "Pleadings, discovery, motions, trial prep — civil disputes", "category": "legal", "category_name": "Legal materials", "family": "finance-legal", "family_name": "Finance and law", "adaptation_state": "described", "tasks": [ "Pleadings, discovery, motions, trial prep — civil disputes" ], "methods": [ "Source review, issue mapping and document preparation" ], "outputs": [ "Draft for an authorized specialist" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "beautifulsoup4", "jinja2", "lxml", "pandas", "pandoc", "pdfplumber", "poppler-utils", "python-docx", "requests" ], "required_skills": [ "skill-pleading-drafting", "skill-discovery-ediscovery", "skill-legal-research" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-litigation-attorney/professional.json", "source_id": "prof-litigation-attorney", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "325892b65b0092abf9b638369d27c7af182b495b1e4ac746373d03e71980807a", "role_sha256": "4faf4a1b30d07305a3e83cc49af4cda62e109efbd6fa085c48973f7960881e07", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "fetch", "searxng", "brave-search" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-llm-engineer", "name": "LLM Application Engineer", "description": "Prompt engineering, RAG, agent design, eval pipelines", "category": "data", "category_name": "Data", "family": "data-ai", "family_name": "Data and AI", "adaptation_state": "described", "tasks": [ "Prompt engineering, RAG, agent design, eval pipelines" ], "methods": [ "Data quality checks and reproducible analysis" ], "outputs": [ "Dataset, analysis or model with checks" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "alembic", "anthropic", "asyncpg", "beautifulsoup4", "celery", "chromadb", "crawl4ai", "fastapi", "httpx", "instructor", "langchain", "openai", "postgresql-client", "pydantic", "ragas", "redis", "redis-tools", "sentence-transformers", "sqlalchemy", "tiktoken", "trafilatura", "typescript", "uvicorn" ], "required_skills": [ "skill-llm-engineering", "skill-backend-services", "skill-web-research" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-llm-engineer/professional.json", "source_id": "prof-llm-engineer", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "6f845184c3b41daa4f9a515ded8723f6877961703c725f7de951c085ecd0ad88", "role_sha256": "ed6fa4ca6c40f9b94fbd8102fce708216760c592c576a2e4f1ee94abc270ade4", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-m-and-a-attorney", "name": "M&A Attorney", "description": "Due diligence, SPA/APA drafting, regulatory clearance, closing", "category": "legal", "category_name": "Legal materials", "family": "finance-legal", "family_name": "Finance and law", "adaptation_state": "described", "tasks": [ "Due diligence, SPA/APA drafting, regulatory clearance, closing" ], "methods": [ "Source review, issue mapping and document preparation" ], "outputs": [ "Draft for an authorized specialist" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "beautifulsoup4", "jinja2", "lxml", "openpyxl", "pandoc", "pdfplumber", "python-docx", "requests" ], "required_skills": [ "skill-contract-review", "skill-corporate-housekeeping", "skill-legal-research" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-m-and-a-attorney/professional.json", "source_id": "prof-m-and-a-attorney", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "4b986a92b22eab64f9af897381312ec61dadc9ea4256ad58a6dbe2b08bd094d0", "role_sha256": "66000307bb91e674da4b5f0b90ba64eeeb240898b7bb47a903be07e89d9f124a", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "fetch" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-maintenance-manager", "name": "Maintenance and Reliability Manager", "description": "Controls asset criticality, maintenance strategy, work execution, spares and reliability", "category": "manufacturing", "category_name": "Manufacturing", "family": "manufacturing", "family_name": "Manufacturing", "adaptation_state": "described", "tasks": [ "Controls asset criticality, maintenance strategy, work execution, spares and reliability" ], "methods": [ "Capacity planning and controlled improvement" ], "outputs": [ "Feasible production plan" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "matplotlib", "numpy", "openpyxl", "pandas", "python-docx", "scipy" ], "required_skills": [ "skill-facilities-management", "skill-manufacturing-process", "skill-data-analysis" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-maintenance-manager/professional.json", "source_id": "prof-maintenance-manager", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "46ac769594622e2037e62c2e4223082c831d6f49b8c3fe708f15aa64a41a8fa0", "role_sha256": "acd70224d2084b7f127c337e658ebde53d305752c2c03cfcbdf91e267d9d718e", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-malware-analyst", "name": "Malware Analyst / Reverse Engineer", "description": "Static/dynamic analysis, unpacking, IOC extraction", "category": "security", "category_name": "Defensive security", "family": "cyber-risk", "family_name": "Cyber risk", "adaptation_state": "described", "tasks": [ "Static/dynamic analysis, unpacking, IOC extraction" ], "methods": [ "Authorized assessment and evidence review" ], "outputs": [ "Defensive findings and remediation plan" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "binwalk", "capstone", "dnsutils", "ffuf", "foremost", "gdb", "gdb-multiarch", "git", "gobuster", "keystone-engine", "lief", "masscan", "netcat-openbsd", "nmap", "pwntools", "python-nmap", "radare2", "recon-ng", "scapy", "semgrep", "sleuthkit", "theharvester", "unicorn", "whois" ], "required_skills": [ "skill-security-audit", "skill-reverse-engineering", "skill-pentest-recon", "skill-osint" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-malware-analyst/professional.json", "source_id": "prof-malware-analyst", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "9c7cf57e4e97e5f69a58f17ed2d713c9568fab22f5a2c43803325072ffc3b67f", "role_sha256": "36191c2df04338c537ca7bceaea2e5ceed6850769ed5700fc36de84dda894b20", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-manufacturing-engineer", "name": "Manufacturing Engineer", "description": "Designs and improves production methods, tooling, capacity and controlled process changes", "category": "manufacturing", "category_name": "Manufacturing", "family": "manufacturing", "family_name": "Manufacturing", "adaptation_state": "described", "tasks": [ "Designs and improves production methods, tooling, capacity and controlled process changes" ], "methods": [ "Capacity planning and controlled improvement" ], "outputs": [ "Feasible production plan" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "matplotlib", "numpy", "openpyxl", "pandas", "python-docx", "scipy" ], "required_skills": [ "skill-manufacturing-process", "skill-quality-management", "skill-data-analysis" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-manufacturing-engineer/professional.json", "source_id": "prof-manufacturing-engineer", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "d113d0e7429dabc37eb749d606780b89010c456dca201a3c238c4f4c110963e8", "role_sha256": "ec1f6548399e52206c3b4d0e78b4f0047708fe0bd939282a0df89c679eb2d87e", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-market-data-engineer", "name": "Market Data Engineer (feeds, storage, quality, point-in-time datasets)", "description": "Builds and runs the organisation's market and on-chain data layer: venue and chain feeds, normalised storage, point-in-time snapshots, quality checks and access for research, execution and reporting", "category": "data", "category_name": "Data", "family": "data-ai", "family_name": "Data and AI", "adaptation_state": "described", "tasks": [ "Builds and runs the organisation's market and on-chain data layer: venue and chain feeds, normalised storage, point-in-time snapshots, quality checks and access for research, execution and reporting" ], "methods": [ "Data quality checks and reproducible analysis" ], "outputs": [ "Dataset, analysis or model with checks" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "aiohttp", "ccxt", "duckdb", "great-expectations", "pandas", "polars", "pyarrow", "sqlalchemy", "websockets" ], "required_skills": [ "skill-backend-services", "skill-data-analysis", "skill-sysadmin" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-market-data-engineer/professional.json", "source_id": "prof-market-data-engineer", "source_version": "1.0.0", "source_lifecycle": "published", "manifest_sha256": "ee9f8479ed80add99e2f6b273dac0d3094a07e0d9d1b8fcb3bef44f93a8e446b", "role_sha256": "f4067753edbed2dd790a0c4215cf637abcf504bc7956123c9ff4f7f8bb421afe", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "fetch", "sqlite", "postgres" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-medical-coder", "name": "Medical Coder / Biller", "description": "ICD-10-CM / CPT / HCPCS / DRG coding, claims, denials", "category": "compliance", "category_name": "Compliance", "family": "cyber-risk", "family_name": "Cyber risk", "adaptation_state": "described", "tasks": [ "ICD-10-CM / CPT / HCPCS / DRG coding, claims, denials" ], "methods": [ "Requirements mapping and control assessment" ], "outputs": [ "Requirements register and assessment" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "matplotlib", "numpy", "openpyxl", "pandas", "pandoc", "poppler-utils", "scipy", "tesseract-ocr" ], "required_skills": [ "skill-medical-coding-quality", "skill-pdf-extraction", "skill-data-analysis" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-medical-coder/professional.json", "source_id": "prof-medical-coder", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "2c1751b5f0fd3f664a2fe0097f982d6f372d53d76266fe8cd8bcd0152a468bb5", "role_sha256": "3cb8c56eead028d44ec76e8897e979b00b6821883a3a5cfa89a7e989e0a29a08", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "fetch", "sqlite" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-mep-coordinator", "name": "MEP Coordinator", "description": "Coordinates mechanical, electrical and plumbing requirements, interfaces and commissioning", "category": "architecture", "category_name": "Architecture", "family": "built-environment", "family_name": "Built environment", "adaptation_state": "described", "tasks": [ "Coordinates mechanical, electrical and plumbing requirements, interfaces and commissioning" ], "methods": [ "Requirements and interface coordination" ], "outputs": [ "Coordinated design requirements" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "ifcopenshell", "numpy", "openpyxl", "pandas", "pandoc", "python-docx", "scipy" ], "required_skills": [ "skill-bim-coordination", "skill-project-controls", "skill-quality-management" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-mep-coordinator/professional.json", "source_id": "prof-mep-coordinator", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "325bea1f07d555ae65cc117b6bfc6fda494b327320d54fd3da6e655301cd0235", "role_sha256": "f16e4fac617be3cd50ee681b6750e6766f414a7f1231ce35c89f5a2ba59b9a09", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-mev-searcher", "name": "Transaction-ordering Researcher", "description": "Studies extractable value, arbitrage and liquidations in blockchain networks within an explicit mandate.", "category": "engineering", "category_name": "Software engineering", "family": "technology", "family_name": "Technology", "adaptation_state": "described", "tasks": [ "Studies extractable value, arbitrage and liquidations in blockchain networks within an explicit mandate." ], "methods": [ "Requirements, implementation and testing" ], "outputs": [ "Software change with test evidence" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "arelle-release", "datasette", "duckdb", "fixparser", "git", "ibis-framework", "matplotlib", "pandas", "plotly", "polars", "postgresql-client", "pycountry", "python-iso20022", "schwifty", "seaborn", "semgrep", "sepaxml", "sqlite3", "streamlit" ], "required_skills": [ "skill-security-audit", "skill-financial-systems", "skill-bi-dashboards" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-mev-searcher/professional.json", "source_id": "prof-mev-searcher", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "c32545d11c78663ceebf7b98c63d0abf570b7d700ee2255ab54e1e72aeb19005", "role_sha256": "bd86dd8acd8d56bc65a0313e83a2bb3dabbfba8efa40d32971227ba3352e59b2", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-ml-engineer", "name": "ML Engineer", "description": "Pipeline design, model training, deployment, monitoring", "category": "data", "category_name": "Data", "family": "data-ai", "family_name": "Data and AI", "adaptation_state": "described", "tasks": [ "Pipeline design, model training, deployment, monitoring" ], "methods": [ "Data quality checks and reproducible analysis" ], "outputs": [ "Dataset, analysis or model with checks" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "anthropic", "aws-cdk", "build-essential", "cdktf", "chromadb", "instructor", "langchain", "libopenblas-dev", "lightgbm", "matplotlib", "mlflow", "numpy", "openai", "optuna", "pandas", "pulumi", "python-terraform", "ragas", "scikit-learn", "scipy", "sentence-transformers", "statsmodels", "tiktoken", "torch", "unzip", "xgboost" ], "required_skills": [ "skill-ml-modeling", "skill-data-analysis", "skill-llm-engineering", "skill-iac" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-ml-engineer/professional.json", "source_id": "prof-ml-engineer", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "1fff7754b0783a1588f7774e407cfa73fd03f6b083204cb125e25cb011954fe3", "role_sha256": "4ffe9a0e56e25a26cbfaba84a9ce3bdba72089ce2a0d6fc6ed74d16e8d807829", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "github", "postgres", "fetch" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-mobile-engineer", "name": "Mobile Engineer", "description": "React Native / Flutter / native Android", "category": "engineering", "category_name": "Software engineering", "family": "technology", "family_name": "Technology", "adaptation_state": "described", "tasks": [ "React Native / Flutter / native Android" ], "methods": [ "Requirements, implementation and testing" ], "outputs": [ "Software change with test evidence" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "@expo/cli", "alembic", "android-tools-adb", "asyncpg", "celery", "create-next-app", "eas-cli", "eslint", "fastapi", "httpx", "openjdk-17-jdk", "postgresql-client", "prettier", "pydantic", "react-native-cli", "redis", "redis-tools", "sqlalchemy", "typescript", "uvicorn", "vite" ], "required_skills": [ "skill-mobile-android", "skill-backend-services", "skill-frontend-modern" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-mobile-engineer/professional.json", "source_id": "prof-mobile-engineer", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "f9889cf70c0fa353c7c9b862a285e05f8f68883c0873d5988a0f5925f191a55c", "role_sha256": "f6599c6e88226dd36290d2233268c3089ed6642412b569769bbeb81dfa2c8190", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-network-engineer", "name": "Network Engineer", "description": "Routing, switching, VPN, firewall, traffic analysis", "category": "infra", "category_name": "Infrastructure", "family": "technology", "family_name": "Technology", "adaptation_state": "described", "tasks": [ "Routing, switching, VPN, firewall, traffic analysis" ], "methods": [ "Change planning, monitoring and recovery review" ], "outputs": [ "Change plan or operational report" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "ansible-core", "borgbackup", "dnspython", "fabric", "fail2ban", "ffuf", "frr", "gobuster", "iproute2", "logrotate", "masscan", "mitmproxy", "mtr", "netmiko", "nmap", "openvpn", "paramiko", "prometheus-node-exporter", "python-nmap", "recon-ng", "restic", "scapy", "tcpdump", "theharvester", "tshark", "ufw", "wireguard-tools" ], "required_skills": [ "skill-network-engineering", "skill-sysadmin", "skill-pentest-recon" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-network-engineer/professional.json", "source_id": "prof-network-engineer", "source_version": "1.4.1", "source_lifecycle": "published", "manifest_sha256": "9d116fd51c4ac1836fbfb26eb724e0d27aef77be10c93a5661a88e709ed8ef9e", "role_sha256": "51760a7583353be32526376e3fd3216cb7232a1cd2cabee5238f90c0965157ad", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-notary", "name": "Notarial Document Specialist", "description": "Prepares acknowledgement, signing, apostille and remote-process materials for an authorized practitioner.", "category": "support", "category_name": "Support", "family": "people-service", "family_name": "People and service", "adaptation_state": "described", "tasks": [ "Prepares acknowledgement, signing, apostille and remote-process materials for an authorized practitioner." ], "methods": [ "Request triage, resolution checks and escalation" ], "outputs": [ "Resolved request or explicit handover" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "pandoc", "pdfplumber", "poppler-utils", "python-docx", "tesseract-ocr" ], "required_skills": [ "skill-notarial-workflow", "skill-contract-review", "skill-pdf-extraction" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-notary/professional.json", "source_id": "prof-notary", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "b76bf07f095cf7742c4d00329414525d0caff116800bcf30b8b76e8e679d5722", "role_sha256": "d352a5ce14b0feeb5b2289b0edc7ee71b945ab2f4f9e6cc6922303e960f5711d", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "fetch" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-onchain-investigator", "name": "On-chain Investigator (Crypto Forensics)", "description": "Wallet attribution, fund tracing, hack post-mortems, sanctions screening — Chainalysis / TRM / Arkham / Dune style", "category": "osint", "category_name": "Open-source research", "family": "research-media", "family_name": "Research and media", "adaptation_state": "described", "tasks": [ "Wallet attribution, fund tracing, hack post-mortems, sanctions screening — Chainalysis / TRM / Arkham / Dune style" ], "methods": [ "Source verification and evidence correlation" ], "outputs": [ "Evidence-backed research report" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "beautifulsoup4", "datasette", "dnsutils", "duckdb", "ibis-framework", "matplotlib", "pandas", "plotly", "polars", "postgresql-client", "requests", "seaborn", "sqlite3", "streamlit", "whois" ], "required_skills": [ "skill-osint-investigation", "skill-bi-dashboards" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-onchain-investigator/professional.json", "source_id": "prof-onchain-investigator", "source_version": "1.5.0", "source_lifecycle": "published", "manifest_sha256": "79adf84323514af4aeeaa09e462a0b577cd3fef58d6b13df7a0bcca5db7e74be", "role_sha256": "2adb4d41f56c4304cedf3c1771200e5502fe61ff9eaf8e9025c957e3c10b724c", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-online-poker-player", "name": "Poker Strategy Analyst", "description": "Studies strategies, game data and allocated-resource limits without promising returns.", "category": "finance", "category_name": "Finance", "family": "finance-legal", "family_name": "Finance and law", "adaptation_state": "described", "tasks": [ "Studies strategies, game data and allocated-resource limits without promising returns." ], "methods": [ "Reconciliation, scenario analysis and limit review" ], "outputs": [ "Financial model or report with assumptions" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "arelle-release", "fixparser", "pycountry", "python-iso20022", "schwifty", "sepaxml" ], "required_skills": [ "skill-financial-systems" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-online-poker-player/professional.json", "source_id": "prof-online-poker-player", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "61e1cef0862b8e3c995607c2925ae3d938502c60350a8c5f596e727c3ed3321b", "role_sha256": "f1f20037ab45679b2b5b14fa2779b858a0910e848c655b504cd538f3283c321b", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-operations-manager", "name": "Operations Manager / COO (processes, capacity, execution discipline)", "description": "Runs the organisation day to day: operating rhythm, processes and their owners, capacity and bottlenecks, incidents and continuous improvement; makes sure decisions become work and work becomes results", "category": "operations", "category_name": "Operations", "family": "business", "family_name": "Business operations", "adaptation_state": "described", "tasks": [ "Runs the organisation day to day: operating rhythm, processes and their owners, capacity and bottlenecks, incidents and continuous improvement; makes sure decisions become work and work becomes results" ], "methods": [ "Process mapping and exception review" ], "outputs": [ "Operating plan and obligation register" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "matplotlib", "openpyxl", "pandas" ], "required_skills": [ "skill-project-controls", "skill-business-analysis", "skill-business-writing", "skill-data-analysis" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-operations-manager/professional.json", "source_id": "prof-operations-manager", "source_version": "1.0.0", "source_lifecycle": "published", "manifest_sha256": "7764ae9e47f0a852802de06ee2b1bc33d71a4e7a79912204d3da575bca4a81b7", "role_sha256": "8f0daba97fd222afebbde7b2c6d0e6b8e27798580fdd0b06b4b8ddedaccd6428", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "fetch" ], "optional": [] } }, "related_scenarios": [ "support-department-transfer", "resource-allocator", "existing-business-transition" ] }, { "id": "prof-osint-analyst", "name": "Open-source Research Analyst", "description": "Researches organizations, people, domains and infrastructure through permitted open sources.", "category": "security", "category_name": "Defensive security", "family": "cyber-risk", "family_name": "Cyber risk", "adaptation_state": "described", "tasks": [ "Researches organizations, people, domains and infrastructure through permitted open sources." ], "methods": [ "Authorized assessment and evidence review" ], "outputs": [ "Defensive findings and remediation plan" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "beautifulsoup4", "crawl4ai", "dnsutils", "netcat-openbsd", "nmap", "trafilatura", "whois" ], "required_skills": [ "skill-osint", "skill-web-research" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-osint-analyst/professional.json", "source_id": "prof-osint-analyst", "source_version": "1.4.1", "source_lifecycle": "published", "manifest_sha256": "63bc5e2de7bd0f30020fe5418eceb17164bb71d4f3810659622699fb7dcbb5d1", "role_sha256": "4b1bc07b1e8514f2a5eae81ee332c3e01130351488b42c995861a8186495679d", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "fetch", "brave-search", "searxng", "puppeteer" ], "optional": [] } }, "related_scenarios": [ "public-monitor" ] }, { "id": "prof-paralegal", "name": "Paralegal (legal operations, documents, registers, deadlines)", "description": "Runs the legal machinery under counsel: document preparation and management, contract registers and obligations, corporate records and filings, deadlines and evidence, research support; precise, organised, never gives legal advice", "category": "legal", "category_name": "Legal materials", "family": "finance-legal", "family_name": "Finance and law", "adaptation_state": "described", "tasks": [ "Runs the legal machinery under counsel: document preparation and management, contract registers and obligations, corporate records and filings, deadlines and evidence, research support; precise, organised, never gives legal advice" ], "methods": [ "Source review, issue mapping and document preparation" ], "outputs": [ "Draft for an authorized specialist" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "openpyxl", "pandas", "pdfplumber", "python-docx" ], "required_skills": [ "skill-legal-research", "skill-contract-review", "skill-pdf-extraction", "skill-business-writing" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-paralegal/professional.json", "source_id": "prof-paralegal", "source_version": "1.0.0", "source_lifecycle": "published", "manifest_sha256": "e00a7c4c0a6c8c8e5cc75bdd615878f9689a460b8b41d4dd493e232f07cb27e0", "role_sha256": "728aa31dc182e1372f3eb78dbd05150e034ab73b53144e8c6b01ebf7247e2683", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "fetch", "searxng" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-partnerships-manager", "name": "Partnerships & Business Development Manager (alliances, channels, joint value)", "description": "Finds, structures and grows partnerships that create value for both sides: channel and technology partners, integrations, co-marketing and distribution deals; owns partner selection, agreements within policy and the health of each relationship", "category": "sales", "category_name": "Sales", "family": "commercial", "family_name": "Commercial work", "adaptation_state": "described", "tasks": [ "Finds, structures and grows partnerships that create value for both sides: channel and technology partners, integrations, co-marketing and distribution deals; owns partner selection, agreements within policy and the health of each relationship" ], "methods": [ "Needs discovery and evidence-based pipeline review" ], "outputs": [ "Proposal and documented handover" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "pandas", "python-docx" ], "required_skills": [ "skill-business-writing", "skill-business-analysis", "skill-contract-review", "skill-web-research" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-partnerships-manager/professional.json", "source_id": "prof-partnerships-manager", "source_version": "1.0.0", "source_lifecycle": "published", "manifest_sha256": "097d0b6568308a7a14ae7296ca36edc94a71fb25122f81623a3d8bec4b439d01", "role_sha256": "4bc17513621eaa7a46cb91a780e0abef360d79b636c5608d4cdbc012916a9395", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "fetch", "searxng" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-pentester", "name": "Security Assessment Specialist", "description": "Performs authorized application and network security assessment and prepares defensive reports.", "category": "security", "category_name": "Defensive security", "family": "cyber-risk", "family_name": "Cyber risk", "adaptation_state": "described", "tasks": [ "Performs authorized application and network security assessment and prepares defensive reports." ], "methods": [ "Authorized assessment and evidence review" ], "outputs": [ "Defensive findings and remediation plan" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "beautifulsoup4", "crawl4ai", "dnsutils", "ffuf", "git", "gobuster", "httpx", "masscan", "mitmproxy", "netcat-openbsd", "nikto", "nmap", "python-nmap", "recon-ng", "requests", "scapy", "semgrep", "sqlmap", "theharvester", "trafilatura", "wfuzz", "whatweb", "whois" ], "required_skills": [ "skill-security-audit", "skill-pentest-recon", "skill-web-security", "skill-osint", "skill-web-research" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-pentester/professional.json", "source_id": "prof-pentester", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "469e4bd95ae59cdca918bf3e5f65a5198c360461a289938b17ca80f886328c90", "role_sha256": "18576e26138e432b139340172327b2efe100d41c85d797edfc4dcdbd9d3d568d", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-performance-marketer", "name": "Performance Marketer (PPC / paid)", "description": "Google / Meta / TikTok / LinkedIn ads, conversion tracking, LTV/CAC", "category": "marketing", "category_name": "Marketing", "family": "commercial", "family_name": "Commercial work", "adaptation_state": "described", "tasks": [ "Google / Meta / TikTok / LinkedIn ads, conversion tracking, LTV/CAC" ], "methods": [ "Audience research and measured experiments" ], "outputs": [ "Campaign plan and results analysis" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "matplotlib", "numpy", "pandas", "scipy" ], "required_skills": [ "skill-data-analysis" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-performance-marketer/professional.json", "source_id": "prof-performance-marketer", "source_version": "1.4.1", "source_lifecycle": "published", "manifest_sha256": "de7523875b2db38d112cabf21e9e763be33905ddd1034bd1c0b4037274d632e4", "role_sha256": "b5dca3fa0c732c2f2dfeb09dca8422e05db54c976f0d288472e743c8808f4c73", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "fetch", "postgres", "sqlite" ], "optional": [] } }, "related_scenarios": [ "content-business-loop" ] }, { "id": "prof-pharma-regulatory", "name": "Pharma Regulatory Affairs", "description": "Drug submissions (IND/NDA/BLA, MAA/CTA), labeling, pharmacovigilance", "category": "compliance", "category_name": "Compliance", "family": "cyber-risk", "family_name": "Cyber risk", "adaptation_state": "described", "tasks": [ "Drug submissions (IND/NDA/BLA, MAA/CTA), labeling, pharmacovigilance" ], "methods": [ "Requirements mapping and control assessment" ], "outputs": [ "Requirements register and assessment" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "openpyxl", "pandas", "pandoc", "poppler-utils", "python-docx", "tesseract-ocr" ], "required_skills": [ "skill-pharma-regulatory-submission", "skill-clinical-evidence-operations", "skill-pdf-extraction" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-pharma-regulatory/professional.json", "source_id": "prof-pharma-regulatory", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "14f22929bcf3a95b478483a1e58009d272051a0e534d9f7da74032e6718eb468", "role_sha256": "48cbc395db82c38830ebf7d1cb3399ee654934fd50476950755984353aa04394", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "fetch", "searxng" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-platform-engineer", "name": "Platform Engineer", "description": "Internal developer platforms, golden paths, tooling", "category": "infra", "category_name": "Infrastructure", "family": "technology", "family_name": "Technology", "adaptation_state": "described", "tasks": [ "Internal developer platforms, golden paths, tooling" ], "methods": [ "Change planning, monitoring and recovery review" ], "outputs": [ "Change plan or operational report" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "alembic", "asyncpg", "aws-cdk", "cdktf", "celery", "fastapi", "grafana-api", "httpx", "jq", "kubernetes", "opentelemetry-api", "opentelemetry-sdk", "postgresql-client", "prometheus-client", "prometheus-node-exporter", "pulumi", "pydantic", "python-terraform", "pyyaml", "redis", "redis-tools", "sqlalchemy", "typescript", "unzip", "uvicorn" ], "required_skills": [ "skill-iac", "skill-k8s", "skill-backend-services", "skill-monitoring" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-platform-engineer/professional.json", "source_id": "prof-platform-engineer", "source_version": "1.4.1", "source_lifecycle": "published", "manifest_sha256": "c6dc039eff736c6c91e98ad4e48aa0bb5aa9cdae1e7a76313f45c2a352a96c8a", "role_sha256": "ea04f4e48e44ccd35c7b14fc3128ec7a7fc7f79685bee5f6c4d0e663ad29d8a7", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "github", "gitlab", "postgres", "fetch" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-policy-analyst", "name": "Policy Analyst / Government Relations", "description": "Legislative tracking, regulatory comments, impact assessment, lobbying", "category": "research", "category_name": "Research", "family": "research-media", "family_name": "Research and media", "adaptation_state": "described", "tasks": [ "Legislative tracking, regulatory comments, impact assessment, lobbying" ], "methods": [ "Question framing, source evaluation and hypothesis tests" ], "outputs": [ "Report with sources and uncertainty" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "beautifulsoup4", "crawl4ai", "lxml", "pandoc", "requests", "trafilatura" ], "required_skills": [ "skill-legal-research", "skill-web-research" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-policy-analyst/professional.json", "source_id": "prof-policy-analyst", "source_version": "1.4.1", "source_lifecycle": "published", "manifest_sha256": "92f2c790653feda81429bb0050a688f17ef3d40b7d50463e58be92a82ec3a10c", "role_sha256": "7b5073486570b7d6bf1acc7d970aec149ee41f91c133c14333e7572452ac0afa", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "fetch", "searxng" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-portfolio-manager", "name": "Portfolio Manager (allocation, sizing, mandate discipline)", "description": "Owns the portfolio as a whole: allocation across strategies and assets, sizing within the mandate, rebalancing and performance attribution; decides what capital goes where and why, within limits set by risk and the owner", "category": "finance", "category_name": "Finance", "family": "finance-legal", "family_name": "Finance and law", "adaptation_state": "described", "tasks": [ "Owns the portfolio as a whole: allocation across strategies and assets, sizing within the mandate, rebalancing and performance attribution; decides what capital goes where and why, within limits set by risk and the owner" ], "methods": [ "Reconciliation, scenario analysis and limit review" ], "outputs": [ "Financial model or report with assumptions" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "duckdb", "matplotlib", "numpy", "pandas", "pyportfolioopt", "riskfolio-lib", "scipy" ], "required_skills": [ "skill-financial-systems", "skill-data-analysis", "skill-bi-dashboards", "skill-risk-analysis" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-portfolio-manager/professional.json", "source_id": "prof-portfolio-manager", "source_version": "1.0.0", "source_lifecycle": "published", "manifest_sha256": "301d8faf55ee23cf9b92f08daae844272b9eb5c1a84502a51f63df0547bc3f3d", "role_sha256": "02d25301a61cb59557de89c0eebcc28f8dde4c5066074ed4ef1e5cafa4c28178", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "fetch", "sqlite" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-pr-communications-manager", "name": "PR & Communications Manager (messaging, media, announcements, crisis communication)", "description": "Owns what the organisation says publicly and to stakeholders: messaging and positioning, press and analyst relations, announcements and statements, spokesperson preparation and crisis communication; every public claim approved and sourced", "category": "marketing", "category_name": "Marketing", "family": "commercial", "family_name": "Commercial work", "adaptation_state": "described", "tasks": [ "Owns what the organisation says publicly and to stakeholders: messaging and positioning, press and analyst relations, announcements and statements, spokesperson preparation and crisis communication; every public claim approved and sourced" ], "methods": [ "Audience research and measured experiments" ], "outputs": [ "Campaign plan and results analysis" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "pandas", "python-docx" ], "required_skills": [ "skill-business-writing", "skill-content-writing", "skill-web-research" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-pr-communications-manager/professional.json", "source_id": "prof-pr-communications-manager", "source_version": "1.0.0", "source_lifecycle": "published", "manifest_sha256": "dddf0c732ce3f8a13fe67fc91e5be3b8dda153ade0e28108c52d219afa3230a1", "role_sha256": "21b3a69f1eb935c353640e5afe0e115903accdfed33a6c043e2fb01912a8dfcb", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "fetch", "searxng" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-prediction-market-trader", "name": "Prediction Market Analyst", "description": "Studies event prices and probabilities within explicit constraints.", "category": "finance", "category_name": "Finance", "family": "finance-legal", "family_name": "Finance and law", "adaptation_state": "described", "tasks": [ "Studies event prices and probabilities within explicit constraints." ], "methods": [ "Reconciliation, scenario analysis and limit review" ], "outputs": [ "Financial model or report with assumptions" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "arelle-release", "datasette", "duckdb", "fixparser", "ibis-framework", "matplotlib", "pandas", "plotly", "polars", "postgresql-client", "pycountry", "python-iso20022", "schwifty", "seaborn", "sepaxml", "sqlite3", "streamlit" ], "required_skills": [ "skill-financial-systems", "skill-bi-dashboards" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-prediction-market-trader/professional.json", "source_id": "prof-prediction-market-trader", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "bd33eb6df4e1d9bf149e6b5dff508a71e8bdad7e23b1cba1662586981ef9a832", "role_sha256": "e2052434f2a4ca533aba3078ecba74ef681459630db8d189ea850c83bec213be", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-private-investigator", "name": "Private Investigator / Due Diligence", "description": "Background checks, asset tracing, surveillance ethics, pre-litigation", "category": "security", "category_name": "Defensive security", "family": "cyber-risk", "family_name": "Cyber risk", "adaptation_state": "described", "tasks": [ "Background checks, asset tracing, surveillance ethics, pre-litigation" ], "methods": [ "Authorized assessment and evidence review" ], "outputs": [ "Defensive findings and remediation plan" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "beautifulsoup4", "crawl4ai", "dnsutils", "netcat-openbsd", "nmap", "trafilatura", "whois" ], "required_skills": [ "skill-osint", "skill-web-research" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-private-investigator/professional.json", "source_id": "prof-private-investigator", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "ed597c9c6b7af2f26e7e8770afc2da69990b9a8bc7ed4896513846546832cef1", "role_sha256": "29cea3e58034c8f41741c051c9f0d76a82e3548e33817c453ff3d90f20d33827", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "fetch", "searxng", "brave-search", "puppeteer" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-procurement", "name": "Procurement / Vendor Manager", "description": "RFQ, vendor DD, contract negotiation, performance monitoring", "category": "procurement", "category_name": "Procurement", "family": "supply-chain", "family_name": "Supply chains", "adaptation_state": "described", "tasks": [ "RFQ, vendor DD, contract negotiation, performance monitoring" ], "methods": [ "Supplier comparison and obligation review" ], "outputs": [ "Sourcing recommendation with evidence" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "beautifulsoup4", "pandas", "pandoc", "pdfplumber", "python-docx", "requests" ], "required_skills": [ "skill-vendor-due-diligence", "skill-contract-review", "skill-rfq-extraction" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-procurement/professional.json", "source_id": "prof-procurement", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "92d38613259669574809f95a6be4f3721e014d1afb8ee0e386af8be74df9dc92", "role_sha256": "60b7c9162e2a8970eeb8f215ec7468ce961c4116eab5cf690f5a7ed0c6390ac6", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "fetch", "slack", "gmail" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-product-designer", "name": "Product Designer (UI/UX)", "description": "User flows, wireframes, hi-fi mockups, design systems, prototyping", "category": "product", "category_name": "Product", "family": "business", "family_name": "Business operations", "adaptation_state": "described", "tasks": [ "User flows, wireframes, hi-fi mockups, design systems, prototyping" ], "methods": [ "User research, prioritization and prototyping" ], "outputs": [ "Requirements, prototype or research findings" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "create-next-app", "eslint", "openpyxl", "pandas", "prettier", "typescript", "vite" ], "required_skills": [ "skill-product-design", "skill-product-discovery", "skill-frontend-modern" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-product-designer/professional.json", "source_id": "prof-product-designer", "source_version": "1.4.1", "source_lifecycle": "published", "manifest_sha256": "5f0a3ad2e2421e381e3f6b49a13efea9e384e4dfd269127b58d510a8680d750f", "role_sha256": "560859f01c5b6864ac1dac7b083af1d378ecc9b57623b2a3ab17cbffc8d2da6e", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "notion", "linear", "fetch" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-product-manager", "name": "Product Manager", "description": "Discovery, roadmap, OKRs, PRD, prioritization, stakeholder mgmt", "category": "product", "category_name": "Product", "family": "business", "family_name": "Business operations", "adaptation_state": "described", "tasks": [ "Discovery, roadmap, OKRs, PRD, prioritization, stakeholder mgmt" ], "methods": [ "User research, prioritization and prototyping" ], "outputs": [ "Requirements, prototype or research findings" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "openpyxl", "pandas", "pandoc", "python-docx" ], "required_skills": [ "skill-product-discovery", "skill-business-analysis", "skill-business-writing" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-product-manager/professional.json", "source_id": "prof-product-manager", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "73f38a9af1a87e13d17b582a1b9dcb0fdedc240e741efafbb1de88d127154989", "role_sha256": "4f9e8b9380641e9eff61421b164172fbea585e904e3a56613c9323d7f2a64db3", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "notion", "linear", "slack", "fetch" ], "optional": [] } }, "related_scenarios": [ "business-discovery" ] }, { "id": "prof-production-manager", "name": "Production Manager", "description": "Owns safe daily production, staffing, schedule attainment, quality and escalation", "category": "manufacturing", "category_name": "Manufacturing", "family": "manufacturing", "family_name": "Manufacturing", "adaptation_state": "described", "tasks": [ "Owns safe daily production, staffing, schedule attainment, quality and escalation" ], "methods": [ "Capacity planning and controlled improvement" ], "outputs": [ "Feasible production plan" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "numpy", "openpyxl", "pandas", "pandoc", "python-docx", "scipy" ], "required_skills": [ "skill-manufacturing-process", "skill-quality-management", "skill-ehs-management", "skill-project-controls" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-production-manager/professional.json", "source_id": "prof-production-manager", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "a248c98bab70bb9ad90683bc333760b398dda3ccdf089885a23147a07869b3dc", "role_sha256": "bb8976b37c8719583147f58156199e11887d0e099c48d053b340283ec297bb68", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-production-planner", "name": "Production Planner", "description": "Creates feasible time-phased production plans from demand, material and capacity constraints", "category": "manufacturing", "category_name": "Manufacturing", "family": "manufacturing", "family_name": "Manufacturing", "adaptation_state": "described", "tasks": [ "Creates feasible time-phased production plans from demand, material and capacity constraints" ], "methods": [ "Capacity planning and controlled improvement" ], "outputs": [ "Feasible production plan" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "matplotlib", "numpy", "openpyxl", "pandas", "python-docx", "scipy", "statsmodels" ], "required_skills": [ "skill-demand-supply-planning", "skill-manufacturing-process", "skill-data-analysis" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-production-planner/professional.json", "source_id": "prof-production-planner", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "a52222a844ae60c06ce7edc7839289960411cbeb3a07129b92b235ca391771fc", "role_sha256": "605f377d7a465ea6af176a3cb529fdf3737d4b0e5d10b9217aba5db23906e384", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-project-manager", "name": "Project Manager / Scrum Master", "description": "Plan, scope, risk, schedule, ceremonies, dependency mgmt", "category": "pm", "category_name": "Project management", "family": "business", "family_name": "Business operations", "adaptation_state": "described", "tasks": [ "Plan, scope, risk, schedule, ceremonies, dependency mgmt" ], "methods": [ "Scope, risk and dependency planning" ], "outputs": [ "Project plan and acceptance record" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "openpyxl", "pandas", "pandoc", "python-docx" ], "required_skills": [ "skill-project-delivery", "skill-business-analysis", "skill-business-writing" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-project-manager/professional.json", "source_id": "prof-project-manager", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "d8e0b02984f109b473e1fab6949f49ffb2aa2e71e0a172812142e9ce09bff9f3", "role_sha256": "6f623aa59a049bffafb2da31c6a68b923bfd70cfa565dc8ad61803706e7473e0", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "linear", "notion", "slack" ], "optional": [] } }, "related_scenarios": [ "software-service", "coordination-office" ] }, { "id": "prof-prompt-engineer", "name": "Prompt Engineer / LLM Optimization", "description": "Prompt design, eval, A/B testing, retrieval, agent scaffolding", "category": "data", "category_name": "Data", "family": "data-ai", "family_name": "Data and AI", "adaptation_state": "described", "tasks": [ "Prompt design, eval, A/B testing, retrieval, agent scaffolding" ], "methods": [ "Data quality checks and reproducible analysis" ], "outputs": [ "Dataset, analysis or model with checks" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "anthropic", "chromadb", "instructor", "langchain", "openai", "ragas", "sentence-transformers", "tiktoken" ], "required_skills": [ "skill-llm-engineering" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-prompt-engineer/professional.json", "source_id": "prof-prompt-engineer", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "3ba1e751b9364812d69fcd2bff9c7669fec31d7881fe121a7761af47840652d0", "role_sha256": "1eca4cce1ba5175297dfb098d9d873b9c0436eda110778faf8bccf7f3be18a54", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "fetch", "github" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-prop-firm-trader", "name": "Proprietary Trading Rules Analyst", "description": "Studies evaluation-program rules, account limits and discipline for allocated funds.", "category": "finance", "category_name": "Finance", "family": "finance-legal", "family_name": "Finance and law", "adaptation_state": "described", "tasks": [ "Studies evaluation-program rules, account limits and discipline for allocated funds." ], "methods": [ "Reconciliation, scenario analysis and limit review" ], "outputs": [ "Financial model or report with assumptions" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "arelle-release", "datasette", "duckdb", "fixparser", "ibis-framework", "matplotlib", "pandas", "plotly", "polars", "postgresql-client", "pycountry", "python-iso20022", "schwifty", "seaborn", "sepaxml", "sqlite3", "streamlit" ], "required_skills": [ "skill-financial-systems", "skill-bi-dashboards" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-prop-firm-trader/professional.json", "source_id": "prof-prop-firm-trader", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "8af341aef7b874aa5f8c1d85543dbb965df854bd46dfb39c87e3b050d95c13ff", "role_sha256": "86c3affcbac721c85b2b4b114539f673db9a71d62327cbff433635269afae298", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-property-manager", "name": "Property Manager", "description": "Administers occupancy, leases, service charges, vendors, maintenance and tenant service", "category": "facilities", "category_name": "Facilities and property", "family": "built-environment", "family_name": "Built environment", "adaptation_state": "described", "tasks": [ "Administers occupancy, leases, service charges, vendors, maintenance and tenant service" ], "methods": [ "Asset registers and service planning" ], "outputs": [ "Maintenance or occupancy plan" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "openpyxl", "pandas", "pandoc", "pdfplumber", "python-docx" ], "required_skills": [ "skill-facilities-management", "skill-contract-administration", "skill-business-writing" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-property-manager/professional.json", "source_id": "prof-property-manager", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "bd447711854487a67847a972416eec3d09b645658bf1124a8ce529f0973d6e17", "role_sha256": "ab3043ea6ca2b3003c2afa7effeeaeb410ea7422a9895b48d25115ecb31745b4", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-qa-engineer", "name": "QA / Test Engineer", "description": "Test pyramid (unit → integration → E2E), automation in CI/CD, performance + security testing gates", "category": "engineering", "category_name": "Software engineering", "family": "technology", "family_name": "Technology", "adaptation_state": "described", "tasks": [ "Test pyramid (unit → integration → E2E), automation in CI/CD, performance + security testing gates" ], "methods": [ "Requirements, implementation and testing" ], "outputs": [ "Software change with test evidence" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "@playwright/test", "cypress", "faker", "httpx", "hypothesis", "k6", "locust", "mitmproxy", "molotov", "nikto", "pytest", "pytest-asyncio", "pytest-xdist", "requests", "sqlmap", "vitest", "wfuzz", "whatweb" ], "required_skills": [ "skill-test-automation", "skill-performance-testing", "skill-web-security" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-qa-engineer/professional.json", "source_id": "prof-qa-engineer", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "6c45189f285e71f6149ffb33fd03e6e784a156c4d72a348cafeea710e65467a9", "role_sha256": "304dd5446d9af2fc66968b9fdbe22909e3ef8b492ed445e88577d735aaebede0", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "github", "puppeteer", "fetch" ], "optional": [] } }, "related_scenarios": [ "game-project" ] }, { "id": "prof-quality-manager", "name": "Quality Manager", "description": "Owns the quality system, assurance, control, audit, nonconformity and improvement evidence", "category": "quality", "category_name": "Quality", "family": "manufacturing", "family_name": "Manufacturing", "adaptation_state": "described", "tasks": [ "Owns the quality system, assurance, control, audit, nonconformity and improvement evidence" ], "methods": [ "Criteria-based checks and corrective action" ], "outputs": [ "Quality assessment and action plan" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "duckdb", "matplotlib", "numpy", "openpyxl", "pandas", "pandoc", "python-docx", "scipy" ], "required_skills": [ "skill-quality-management", "skill-internal-controls", "skill-data-analysis", "skill-business-writing" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-quality-manager/professional.json", "source_id": "prof-quality-manager", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "6839f3803f18ffecf2a4c285971bea59d773c91a8bc88a04c9bc5aa586446b90", "role_sha256": "abacc371191b6a729555355756f49e334e04d0cfcacfe7d44feab35538673dd1", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-quant-researcher", "name": "Quantitative Researcher (systematic strategies, backtesting, alpha research)", "description": "Designs, backtests and validates systematic trading strategies with rigorous statistics; owns the research pipeline from hypothesis to deployable signal, never the live order flow", "category": "finance", "category_name": "Finance", "family": "finance-legal", "family_name": "Finance and law", "adaptation_state": "described", "tasks": [ "Designs, backtests and validates systematic trading strategies with rigorous statistics; owns the research pipeline from hypothesis to deployable signal, never the live order flow" ], "methods": [ "Reconciliation, scenario analysis and limit review" ], "outputs": [ "Financial model or report with assumptions" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "ccxt", "duckdb", "matplotlib", "numpy", "pandas", "polars", "scikit-learn", "scipy", "statsmodels", "vectorbt" ], "required_skills": [ "skill-data-analysis", "skill-financial-systems", "skill-bi-dashboards" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-quant-researcher/professional.json", "source_id": "prof-quant-researcher", "source_version": "1.0.0", "source_lifecycle": "published", "manifest_sha256": "b148f88e9f25e1fdbcb7066e993b61965b786f085594759b166632a585684335", "role_sha256": "80405b69f8d6901de95a5eff06afb7e9dc7515a59f801c62c71afca4beef96e7", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "fetch", "sqlite" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-quantity-surveyor", "name": "Quantity Surveyor", "description": "Manages construction cost planning, measurement, procurement and commercial control", "category": "construction", "category_name": "Construction", "family": "built-environment", "family_name": "Built environment", "adaptation_state": "described", "tasks": [ "Manages construction cost planning, measurement, procurement and commercial control" ], "methods": [ "Planning, coordination and evidence review" ], "outputs": [ "Plans, estimates and completion records" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "matplotlib", "numpy", "openpyxl", "pandas", "pandoc", "pdfplumber", "python-docx", "scipy" ], "required_skills": [ "skill-construction-estimating", "skill-contract-administration", "skill-project-controls", "skill-data-analysis" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-quantity-surveyor/professional.json", "source_id": "prof-quantity-surveyor", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "5d9c825bb28fcfec8df17140fd6c448b193602cad9e408d9dd3181d5c503d1b7", "role_sha256": "b4bf692c0a06bf477501aea7f7a46f81ae039e3021622a5d6dcbc350f6e20473", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-real-estate-agent", "name": "Real Estate Agent / Broker", "description": "Listings, valuations (CMA), showings, offers, escrow, disclosures", "category": "sales", "category_name": "Sales", "family": "commercial", "family_name": "Commercial work", "adaptation_state": "described", "tasks": [ "Listings, valuations (CMA), showings, offers, escrow, disclosures" ], "methods": [ "Needs discovery and evidence-based pipeline review" ], "outputs": [ "Proposal and documented handover" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "beautifulsoup4", "crawl4ai", "openpyxl", "pandoc", "python-docx", "trafilatura" ], "required_skills": [ "skill-real-estate-transactions", "skill-web-research", "skill-business-writing" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-real-estate-agent/professional.json", "source_id": "prof-real-estate-agent", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "6714573f2dcf80ab4a3cae2666d48eb983cc070f0d93fcd8ed70a8674fab08e6", "role_sha256": "0d32e10664791cf16f4b288814bf89e130a517d4d9de7c00d46ae825315e57a4", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "fetch", "google-maps" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-real-estate-attorney", "name": "Real Estate Attorney", "description": "Acquisitions, leasing, financing, title, zoning", "category": "legal", "category_name": "Legal materials", "family": "finance-legal", "family_name": "Finance and law", "adaptation_state": "described", "tasks": [ "Acquisitions, leasing, financing, title, zoning" ], "methods": [ "Source review, issue mapping and document preparation" ], "outputs": [ "Draft for an authorized specialist" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "beautifulsoup4", "jinja2", "lxml", "openpyxl", "pandoc", "pdfplumber", "python-docx", "requests" ], "required_skills": [ "skill-contract-review", "skill-corporate-housekeeping", "skill-legal-research" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-real-estate-attorney/professional.json", "source_id": "prof-real-estate-attorney", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "68fe69c16090a98bc2f879b1ae87daec1507f0af45f274e64c424390dc5a5dc2", "role_sha256": "cf3c476e4672d22db49ea400e66477d7e23cca53c02117986b303b92a0c5365a", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "fetch", "searxng" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-recruiter", "name": "Recruiter / Talent Acquisition", "description": "Sourcing, screening, candidate experience, offer negotiation", "category": "hr", "category_name": "People and learning", "family": "people-service", "family_name": "People and service", "adaptation_state": "described", "tasks": [ "Sourcing, screening, candidate experience, offer negotiation" ], "methods": [ "Needs assessment and structured documentation" ], "outputs": [ "Reviewed personnel or learning materials" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "@google-cloud/local-auth", "google-auth", "google-auth-oauthlib", "googleapis", "openpyxl", "pandoc", "python-docx" ], "required_skills": [ "skill-talent-acquisition", "skill-email-triage", "skill-business-writing" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-recruiter/professional.json", "source_id": "prof-recruiter", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "407fb1178d3cf6b2998054524a08ad16b81aed200d0f635f4252f6b069d258b8", "role_sha256": "0d470d9fde005268e5318b154189a5bc948c6904c24b56b8426930a95b0c94c3", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "fetch", "gmail", "linear" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-regulatory-counsel", "name": "Regulatory / Financial Services Counsel", "description": "Banking/securities/insurance regulation, MiFID II, MiCA, AIFMD, MAR", "category": "legal", "category_name": "Legal materials", "family": "finance-legal", "family_name": "Finance and law", "adaptation_state": "described", "tasks": [ "Banking/securities/insurance regulation, MiFID II, MiCA, AIFMD, MAR" ], "methods": [ "Source review, issue mapping and document preparation" ], "outputs": [ "Draft for an authorized specialist" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "beautifulsoup4", "lxml", "openpyxl", "pandoc", "pdfplumber", "python-docx", "requests" ], "required_skills": [ "skill-legal-research", "skill-securities-disclosure", "skill-contract-review" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-regulatory-counsel/professional.json", "source_id": "prof-regulatory-counsel", "source_version": "1.5.0", "source_lifecycle": "published", "manifest_sha256": "c70b456faf36625e5d4b4925410902086aea802500fa1d9c366f13a55ddaeef2", "role_sha256": "b48c20c39e8c7f8949de5d70cd2fda316f525caf45b4d04c133ff65393409dee", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "fetch", "searxng" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-research-analyst", "name": "Research Analyst", "description": "Researches companies, markets and trends, producing sourced reports.", "category": "research", "category_name": "Research", "family": "research-media", "family_name": "Research and media", "adaptation_state": "described", "tasks": [ "Researches companies, markets and trends, producing sourced reports." ], "methods": [ "Question framing, source evaluation and hypothesis tests" ], "outputs": [ "Report with sources and uncertainty" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "beautifulsoup4", "crawl4ai", "matplotlib", "numpy", "pandas", "pandoc", "poppler-utils", "scipy", "tesseract-ocr", "trafilatura" ], "required_skills": [ "skill-web-research", "skill-data-analysis", "skill-pdf-extraction" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-research-analyst/professional.json", "source_id": "prof-research-analyst", "source_version": "1.5.1", "source_lifecycle": "published", "manifest_sha256": "3b0228a86d9706f2ee4230b90375e3ecd0c6926d6dfbb30947e23d87676c841d", "role_sha256": "e1e2a902c142a00425579964825c1fa2c900f1909f396933b412832f7f5ef656", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem" ], "optional": [] } }, "related_scenarios": [ "personal-research", "new-internal-research", "open-research-lab", "knowledge-commons" ] }, { "id": "prof-risk-manager", "name": "Risk Manager (enterprise)", "description": "ERM, risk register, KRI, scenario, BCP, insurance program", "category": "finance", "category_name": "Finance", "family": "finance-legal", "family_name": "Finance and law", "adaptation_state": "described", "tasks": [ "ERM, risk register, KRI, scenario, BCP, insurance program" ], "methods": [ "Reconciliation, scenario analysis and limit review" ], "outputs": [ "Financial model or report with assumptions" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "duckdb", "matplotlib", "numpy", "openpyxl", "pandas", "scipy" ], "required_skills": [ "skill-risk-analysis", "skill-internal-controls", "skill-data-analysis" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-risk-manager/professional.json", "source_id": "prof-risk-manager", "source_version": "1.5.0", "source_lifecycle": "published", "manifest_sha256": "02ec2172f3e54cce3ced4e79ac7c981a1b00c025d46162f45643f614679b49bf", "role_sha256": "64a1e5d01a7f3ca9a6cf86af32776019842c292f5f172c2315c72e0cd1316413", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "fetch", "sqlite" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-sales-sdr", "name": "Sales Development Specialist", "description": "Enriches lead information and prepares personalized outreach and follow-up.", "category": "sales", "category_name": "Sales", "family": "commercial", "family_name": "Commercial work", "adaptation_state": "described", "tasks": [ "Enriches lead information and prepares personalized outreach and follow-up." ], "methods": [ "Needs discovery and evidence-based pipeline review" ], "outputs": [ "Proposal and documented handover" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "@google-cloud/local-auth", "beautifulsoup4", "crawl4ai", "google-auth", "google-auth-oauthlib", "googleapis", "trafilatura" ], "required_skills": [ "skill-web-research", "skill-email-triage", "skill-content-writing" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-sales-sdr/professional.json", "source_id": "prof-sales-sdr", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "c23463ef91ad581eb4a196c73cdd6ec51f1c9c6aca5580c373897ea6d1850012", "role_sha256": "4a21ce5037470d5497f651721eda8b422cc0c4e1dca9f12401055d66b31da61c", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-security-engineer", "name": "Security Engineer (defensive)", "description": "AppSec / threat modeling / SAST / DAST / SBOM / secret scanning", "category": "security", "category_name": "Defensive security", "family": "cyber-risk", "family_name": "Cyber risk", "adaptation_state": "described", "tasks": [ "AppSec / threat modeling / SAST / DAST / SBOM / secret scanning" ], "methods": [ "Authorized assessment and evidence review" ], "outputs": [ "Defensive findings and remediation plan" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "git", "httpx", "mitmproxy", "nikto", "requests", "semgrep", "sqlmap", "wfuzz", "whatweb" ], "required_skills": [ "skill-security-audit", "skill-web-security" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-security-engineer/professional.json", "source_id": "prof-security-engineer", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "2be2287612d05f39b15516415fdddf473544a63cfc60005393e444d4542724ab", "role_sha256": "4c3406adb4e1415c764ebcf4de182de86d94975f57b0b79a0f465dc457c44fc3", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "fetch", "github", "sentry" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-seo-specialist", "name": "SEO Specialist", "description": "Technical + content + link SEO, GSC, Core Web Vitals, schema.org", "category": "marketing", "category_name": "Marketing", "family": "commercial", "family_name": "Commercial work", "adaptation_state": "described", "tasks": [ "Technical + content + link SEO, GSC, Core Web Vitals, schema.org" ], "methods": [ "Audience research and measured experiments" ], "outputs": [ "Campaign plan and results analysis" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "beautifulsoup4", "crawl4ai", "trafilatura" ], "required_skills": [ "skill-web-research", "skill-content-writing" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-seo-specialist/professional.json", "source_id": "prof-seo-specialist", "source_version": "1.4.1", "source_lifecycle": "published", "manifest_sha256": "3dc7a15ba28b98df7aba6b43b4bc26db14223d1ef41955a2a21a65cb2fee4f24", "role_sha256": "e4bfbf1696e39fb09d1360a1376e6b6b5a7ebfc58f708adb84d4060b24d722b8", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "fetch", "searxng", "brave-search", "puppeteer" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-site-supervisor", "name": "Construction Site Supervisor", "description": "Coordinates daily site work, inspections, constraints, safety and completion evidence", "category": "construction", "category_name": "Construction", "family": "built-environment", "family_name": "Built environment", "adaptation_state": "described", "tasks": [ "Coordinates daily site work, inspections, constraints, safety and completion evidence" ], "methods": [ "Planning, coordination and evidence review" ], "outputs": [ "Plans, estimates and completion records" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "numpy", "openpyxl", "pandas", "pandoc", "python-docx", "scipy" ], "required_skills": [ "skill-project-controls", "skill-ehs-management", "skill-quality-management" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-site-supervisor/professional.json", "source_id": "prof-site-supervisor", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "fa5a634d2ad90817a9ec0ef416bef96eb0847eab554964407b9e09a6f181c725", "role_sha256": "427a735b79db9dfcc9a545e578c5591a3fc9a79dc7c047580e762e2562059a4d", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-smart-contract-auditor", "name": "Smart Contract Auditor (Solidity / Move / Cairo)", "description": "Independent security audit of EVM + non-EVM smart contracts — manual review + automated tools + formal verification", "category": "security", "category_name": "Defensive security", "family": "cyber-risk", "family_name": "Cyber risk", "adaptation_state": "described", "tasks": [ "Independent security audit of EVM + non-EVM smart contracts — manual review + automated tools + formal verification" ], "methods": [ "Authorized assessment and evidence review" ], "outputs": [ "Defensive findings and remediation plan" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "git", "semgrep" ], "required_skills": [ "skill-security-audit", "skill-code-review" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-smart-contract-auditor/professional.json", "source_id": "prof-smart-contract-auditor", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "05265fffdfb51fa2647a86b056ee83ba91b5215544aba0374fba39800f04af3b", "role_sha256": "68c425c69551aafd12969285e547b8e904d6a89d5bada7cae7b25eda6c896b25", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-social-media-manager", "name": "Social Media Manager (channels, calendar, community-facing publishing)", "description": "Owns the organisation's social channels: strategy per channel, content calendar, publishing and scheduling, engagement, brand voice consistency and performance reporting; briefs content production and never publishes unapproved claims", "category": "marketing", "category_name": "Marketing", "family": "commercial", "family_name": "Commercial work", "adaptation_state": "described", "tasks": [ "Owns the organisation's social channels: strategy per channel, content calendar, publishing and scheduling, engagement, brand voice consistency and performance reporting; briefs content production and never publishes unapproved claims" ], "methods": [ "Audience research and measured experiments" ], "outputs": [ "Campaign plan and results analysis" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "matplotlib", "pandas", "python-dateutil" ], "required_skills": [ "skill-content-writing", "skill-business-writing", "skill-data-analysis" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-social-media-manager/professional.json", "source_id": "prof-social-media-manager", "source_version": "1.0.0", "source_lifecycle": "published", "manifest_sha256": "e8ead8866849c0e5d2500c30a97e0001424f6190a4275cda1391314dd0410630", "role_sha256": "4d9d72bffadc135df27e6a550397166e241087a21b749513ac287ddf33574a7d", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "fetch", "searxng" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-sports-bettor", "name": "Sports Market Analyst", "description": "Studies sporting probabilities, prices and model quality without promising winnings.", "category": "finance", "category_name": "Finance", "family": "finance-legal", "family_name": "Finance and law", "adaptation_state": "described", "tasks": [ "Studies sporting probabilities, prices and model quality without promising winnings." ], "methods": [ "Reconciliation, scenario analysis and limit review" ], "outputs": [ "Financial model or report with assumptions" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "arelle-release", "datasette", "duckdb", "fixparser", "ibis-framework", "matplotlib", "pandas", "plotly", "polars", "postgresql-client", "pycountry", "python-iso20022", "schwifty", "seaborn", "sepaxml", "sqlite3", "streamlit" ], "required_skills": [ "skill-financial-systems", "skill-bi-dashboards" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-sports-bettor/professional.json", "source_id": "prof-sports-bettor", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "44193545d56406a39fe9b64a39e21696b87efdc38b4334755be04e127d4be7d8", "role_sha256": "f641988189ba6529e6b508adfad28bdebe203776e41a3991b8053a7357bd3016", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-stablecoin-architect", "name": "Stablecoin Architect", "description": "Design + deploy new stablecoin mechanisms — CDP / algorithmic / RWA-backed / LST-backed (USDe / USDX / sDAI / GHO lineage)", "category": "finance", "category_name": "Finance", "family": "finance-legal", "family_name": "Finance and law", "adaptation_state": "described", "tasks": [ "Design + deploy new stablecoin mechanisms — CDP / algorithmic / RWA-backed / LST-backed (USDe / USDX / sDAI / GHO lineage)" ], "methods": [ "Reconciliation, scenario analysis and limit review" ], "outputs": [ "Financial model or report with assumptions" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "arelle-release", "fixparser", "pycountry", "python-iso20022", "schwifty", "sepaxml" ], "required_skills": [ "skill-financial-systems" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-stablecoin-architect/professional.json", "source_id": "prof-stablecoin-architect", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "4df7ecfcd5166a58c23f3be869e0783924f4ba7d38ebc55bd974e95bf874049e", "role_sha256": "9a0775b5fe658fc21f48e3225d14eb1e72f19b955a5d7a9905c6138555d3d8d4", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-strategic-sourcing-manager", "name": "Strategic Sourcing Manager", "description": "Builds category strategy, runs sourcing events and recommends auditable supplier awards", "category": "procurement", "category_name": "Procurement", "family": "supply-chain", "family_name": "Supply chains", "adaptation_state": "described", "tasks": [ "Builds category strategy, runs sourcing events and recommends auditable supplier awards" ], "methods": [ "Supplier comparison and obligation review" ], "outputs": [ "Sourcing recommendation with evidence" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "beautifulsoup4", "openpyxl", "pandas", "pandoc", "pdfplumber", "python-docx", "requests" ], "required_skills": [ "skill-strategic-sourcing", "skill-supplier-management", "skill-vendor-due-diligence", "skill-contract-review" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-strategic-sourcing-manager/professional.json", "source_id": "prof-strategic-sourcing-manager", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "307a2024d569d0cac7a2264c0ceaca532a005e29466aa9a253bb0790213260d4", "role_sha256": "f62ccd8b899421e060b93d988614105a690a6e0ec95840cae62dc25b6e1e261e", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-structural-engineer", "name": "Structural Engineer", "description": "Reviews structural systems, loads, stability, interfaces and design evidence", "category": "architecture", "category_name": "Architecture", "family": "built-environment", "family_name": "Built environment", "adaptation_state": "described", "tasks": [ "Reviews structural systems, loads, stability, interfaces and design evidence" ], "methods": [ "Requirements and interface coordination" ], "outputs": [ "Coordinated design requirements" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "matplotlib", "numpy", "openpyxl", "pandas", "pandoc", "python-docx", "scipy" ], "required_skills": [ "skill-project-controls", "skill-data-analysis", "skill-business-writing" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-structural-engineer/professional.json", "source_id": "prof-structural-engineer", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "52abaa94ebf78d5abc1479ca817e6981a49129c32758da6d4b033e73c0f75feb", "role_sha256": "063e6ef7dc23b3675b3dc3f6933ec446f9f4c9d0974ff8805fd22530f3241b80", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-supplier-quality-engineer", "name": "Supplier Quality Engineer", "description": "Qualifies suppliers and resolves incoming, process and corrective-action quality risks", "category": "quality", "category_name": "Quality", "family": "manufacturing", "family_name": "Manufacturing", "adaptation_state": "described", "tasks": [ "Qualifies suppliers and resolves incoming, process and corrective-action quality risks" ], "methods": [ "Criteria-based checks and corrective action" ], "outputs": [ "Quality assessment and action plan" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "matplotlib", "numpy", "openpyxl", "pandas", "python-docx", "scipy" ], "required_skills": [ "skill-supplier-management", "skill-quality-management", "skill-data-analysis" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-supplier-quality-engineer/professional.json", "source_id": "prof-supplier-quality-engineer", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "70388bbfa0b7733bd51d67820de4d3acb6a069489574c1dc523e916c2d3ff74c", "role_sha256": "e29d6059a27413e32d6ffe6f1c9cb34ab83cd5faec4af00592888c98be7437ca", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-supply-chain-analyst", "name": "Supply Chain / Logistics Analyst", "description": "Demand planning, inventory, supplier risk, S&OP, Incoterms", "category": "logistics", "category_name": "Logistics", "family": "supply-chain", "family_name": "Supply chains", "adaptation_state": "described", "tasks": [ "Demand planning, inventory, supplier risk, S&OP, Incoterms" ], "methods": [ "Constraint-based planning and delivery tracking" ], "outputs": [ "Transport or warehouse plan" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "matplotlib", "numpy", "pandas", "scipy" ], "required_skills": [ "skill-data-analysis" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-supply-chain-analyst/professional.json", "source_id": "prof-supply-chain-analyst", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "ab24dcd8bd8812266367bbf6f860eaf92f28d493c5cedc0c484e40478673d2cc", "role_sha256": "52ef4e1ed8f22937f71a792f3a74d253765a3c9c872b37925c93bdafe030e15f", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "fetch", "sqlite", "postgres" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-supply-chain-manager", "name": "Supply Chain Manager", "description": "Integrates demand, supply, inventory, logistics, suppliers and resilience decisions", "category": "supply-chain", "category_name": "Supply chains", "family": "supply-chain", "family_name": "Supply chains", "adaptation_state": "described", "tasks": [ "Integrates demand, supply, inventory, logistics, suppliers and resilience decisions" ], "methods": [ "Demand, inventory and supplier analysis" ], "outputs": [ "Supply plan with constraints" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "datasette", "duckdb", "ibis-framework", "matplotlib", "numpy", "openpyxl", "pandas", "pandoc", "plotly", "polars", "postgresql-client", "python-docx", "scipy", "seaborn", "sqlite3", "statsmodels", "streamlit" ], "required_skills": [ "skill-demand-supply-planning", "skill-supplier-management", "skill-project-controls", "skill-bi-dashboards" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-supply-chain-manager/professional.json", "source_id": "prof-supply-chain-manager", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "4e5175178e07ffe63fa8afe0a5c0e5d4ee7b696ca4f4bae65891c453055207ce", "role_sha256": "a48548c564c34aa629cc1ec697b0e7c3c71e7eba9f890e9dba7f0510f6f56cac", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-tax-advisor", "name": "Tax Advisor", "description": "CIT, VAT/GST, withholding, transfer pricing, treaty analysis", "category": "finance", "category_name": "Finance", "family": "finance-legal", "family_name": "Finance and law", "adaptation_state": "described", "tasks": [ "CIT, VAT/GST, withholding, transfer pricing, treaty analysis" ], "methods": [ "Reconciliation, scenario analysis and limit review" ], "outputs": [ "Financial model or report with assumptions" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "beautifulsoup4", "lxml", "openpyxl", "pandas", "pandoc", "python-dateutil", "requests", "sqlalchemy" ], "required_skills": [ "skill-tax-computation", "skill-bookkeeping", "skill-legal-research" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-tax-advisor/professional.json", "source_id": "prof-tax-advisor", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "55753bb62abb31159b7b80de59d70c8426cf5eca0b72ddb2a16b7ac0602eb9b0", "role_sha256": "d6067c3480d72ad3d68460507db063a247d8d01c14887c2bbd638cc1d82e26ea", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "fetch", "searxng" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-tax-attorney", "name": "Tax Attorney", "description": "Structuring, controversy, transfer pricing, treaty analysis (lawyer track)", "category": "legal", "category_name": "Legal materials", "family": "finance-legal", "family_name": "Finance and law", "adaptation_state": "described", "tasks": [ "Structuring, controversy, transfer pricing, treaty analysis (lawyer track)" ], "methods": [ "Source review, issue mapping and document preparation" ], "outputs": [ "Draft for an authorized specialist" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "beautifulsoup4", "lxml", "openpyxl", "pandas", "pandoc", "pdfplumber", "python-dateutil", "python-docx", "requests" ], "required_skills": [ "skill-tax-computation", "skill-legal-research", "skill-contract-review" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-tax-attorney/professional.json", "source_id": "prof-tax-attorney", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "1163f078ed3312e16ca39aeb8ca0944132baca0093bef52a17cd1cecf44a1d8e", "role_sha256": "e6fde9f892d46689597759ba0b28e83c57d38bb752b5b5fba8902f78c5afaed0", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "fetch", "searxng" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-tech-writer", "name": "Tech Writer / Documentation Engineer", "description": "API docs, user guides, README, runbooks, docs-as-code", "category": "content", "category_name": "Content", "family": "research-media", "family_name": "Research and media", "adaptation_state": "described", "tasks": [ "API docs, user guides, README, runbooks, docs-as-code" ], "methods": [ "Source review and editorial iteration" ], "outputs": [ "Reviewable publication draft" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [], "required_skills": [ "skill-content-writing" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-tech-writer/professional.json", "source_id": "prof-tech-writer", "source_version": "1.5.1", "source_lifecycle": "published", "manifest_sha256": "837933925116815d3e815f54cc1f13b6fade1b96b41ae6bc96432bffda83cf2f", "role_sha256": "4da754bed0bf23474f18991fcd45a101b0eed8a99b859528faa14c38bf094886", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "github", "fetch", "notion" ], "optional": [] } }, "related_scenarios": [ "knowledge-commons" ] }, { "id": "prof-tokenomics-designer", "name": "Tokenomics Designer", "description": "Design token supply / distribution / utility / vesting / sink mechanisms — game-theoretic alignment for protocols", "category": "finance", "category_name": "Finance", "family": "finance-legal", "family_name": "Finance and law", "adaptation_state": "described", "tasks": [ "Design token supply / distribution / utility / vesting / sink mechanisms — game-theoretic alignment for protocols" ], "methods": [ "Reconciliation, scenario analysis and limit review" ], "outputs": [ "Financial model or report with assumptions" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "arelle-release", "fixparser", "pycountry", "python-iso20022", "schwifty", "sepaxml" ], "required_skills": [ "skill-financial-systems" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-tokenomics-designer/professional.json", "source_id": "prof-tokenomics-designer", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "fe43578516cfe91e28e04add3bd3e76182ae59d77d7a1df49e2aa6f66599e42e", "role_sha256": "f33f531cc5d3bbe7a82c64364499746414287510733abc6c211d262873985440", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-trader", "name": "Trading Strategy Researcher", "description": "Researches markets, execution, risk and portfolio structure under a mandate without guaranteeing returns.", "category": "finance", "category_name": "Finance", "family": "finance-legal", "family_name": "Finance and law", "adaptation_state": "described", "tasks": [ "Researches markets, execution, risk and portfolio structure under a mandate without guaranteeing returns." ], "methods": [ "Reconciliation, scenario analysis and limit review" ], "outputs": [ "Financial model or report with assumptions" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "arelle-release", "datasette", "duckdb", "fixparser", "ibis-framework", "matplotlib", "pandas", "plotly", "polars", "postgresql-client", "pycountry", "python-iso20022", "schwifty", "seaborn", "sepaxml", "sqlite3", "streamlit" ], "required_skills": [ "skill-financial-systems", "skill-bi-dashboards" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-trader/professional.json", "source_id": "prof-trader", "source_version": "1.5.0", "source_lifecycle": "published", "manifest_sha256": "e90c9e0a70181332bff5ca1bdd66e001db358a4c7b0f33dce28df65a87b65ee8", "role_sha256": "3dc2f18e57ccc6ce7105d6ae2bf5634b1bd09d483fcf752aad24f103ed7dac81", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-translator", "name": "Translator / Localization Engineer", "description": "Human-quality translation + i18n engineering (ICU MessageFormat, RTL, CLDR)", "category": "content", "category_name": "Content", "family": "research-media", "family_name": "Research and media", "adaptation_state": "described", "tasks": [ "Human-quality translation + i18n engineering (ICU MessageFormat, RTL, CLDR)" ], "methods": [ "Source review and editorial iteration" ], "outputs": [ "Reviewable publication draft" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "pandoc", "python-docx" ], "required_skills": [ "skill-translation-localization", "skill-business-writing" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-translator/professional.json", "source_id": "prof-translator", "source_version": "1.4.1", "source_lifecycle": "published", "manifest_sha256": "615c1acad6b2160825a4ff0caa55afe33d6102ba5f7dda3d6800781e1fbfc22c", "role_sha256": "f44aec597a0a0092d326e6baf644f97692f51a780c5a601a6fe618146b78f247", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "fetch" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-treasury-manager", "name": "Treasury Manager", "description": "Cash mgmt, FX hedging, debt, banking relations, intercompany", "category": "finance", "category_name": "Finance", "family": "finance-legal", "family_name": "Finance and law", "adaptation_state": "described", "tasks": [ "Cash mgmt, FX hedging, debt, banking relations, intercompany" ], "methods": [ "Reconciliation, scenario analysis and limit review" ], "outputs": [ "Financial model or report with assumptions" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "arelle-release", "fixparser", "pycountry", "python-iso20022", "schwifty", "sepaxml" ], "required_skills": [ "skill-financial-systems" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-treasury-manager/professional.json", "source_id": "prof-treasury-manager", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "726bdeea6d8e80f9a0ea37a391d797dcda877d00e3f7e6053f13c63e813a8fb5", "role_sha256": "581b9983dd3734a047994a3bfa9f61c7d4d7fb4ca628940aad05f220f7209565", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "fetch", "sqlite" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-trust-estate-attorney", "name": "Trust & Estate Attorney", "description": "Wills, trusts, probate, estate tax, succession planning", "category": "legal", "category_name": "Legal materials", "family": "finance-legal", "family_name": "Finance and law", "adaptation_state": "described", "tasks": [ "Wills, trusts, probate, estate tax, succession planning" ], "methods": [ "Source review, issue mapping and document preparation" ], "outputs": [ "Draft for an authorized specialist" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "beautifulsoup4", "lxml", "pandoc", "pdfplumber", "python-docx", "requests" ], "required_skills": [ "skill-legal-research", "skill-contract-review" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-trust-estate-attorney/professional.json", "source_id": "prof-trust-estate-attorney", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "5e334ec136355a25558b3e0ebcc15572be0f072095a755117be4420545371ce9", "role_sha256": "b1f7a19ad5482c1e0bd4563a290a7f6715ad71f9b78c4adbc629f05cad74498a", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "fetch", "searxng" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-tutor-curriculum", "name": "Tutor / Curriculum Designer", "description": "Subject tutoring + curriculum design (Bloom's, scaffolding, formative assess)", "category": "content", "category_name": "Content", "family": "research-media", "family_name": "Research and media", "adaptation_state": "described", "tasks": [ "Subject tutoring + curriculum design (Bloom's, scaffolding, formative assess)" ], "methods": [ "Source review and editorial iteration" ], "outputs": [ "Reviewable publication draft" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [], "required_skills": [ "skill-content-writing" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-tutor-curriculum/professional.json", "source_id": "prof-tutor-curriculum", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "eebd8d2b128d368241193accd6d8b40ea763756a4c09e6cde771c4bff0199c33", "role_sha256": "3c380f9b6ebb6156a440ffbb93accca5355e7479ac4ba9e8bee881e79562bea9", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "fetch", "notion" ], "optional": [] } }, "related_scenarios": [ "learning-ao" ] }, { "id": "prof-universal", "name": "General Profile", "description": "An unspecialized source profile intended to clarify its role through dialogue and retain the chosen behavior.", "category": "universal", "category_name": "General profile", "family": "general", "family_name": "General", "adaptation_state": "described", "tasks": [ "An unspecialized source profile intended to clarify its role through dialogue and retain the chosen behavior." ], "methods": [ "Clarify purpose before specialization" ], "outputs": [ "A scoped role proposal" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "beautifulsoup4", "crawl4ai", "pandoc", "python-docx", "trafilatura" ], "required_skills": [ "skill-adaptive-task-routing", "skill-web-research", "skill-business-writing" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-universal/professional.json", "source_id": "prof-universal", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "ca4967f667659286b293e9c5693f820cc573a117d0421b29f46daf5542a63477", "role_sha256": "04014ab34b4f07c0bd467af615728d2097c7719044a7c776465f731b05b624cf", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "fetch", "searxng", "brave-search", "puppeteer", "github" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-urban-planner", "name": "Urban and Regional Planner", "description": "Assesses land use, policy, infrastructure, stakeholders and development scenarios", "category": "architecture", "category_name": "Architecture", "family": "built-environment", "family_name": "Built environment", "adaptation_state": "described", "tasks": [ "Assesses land use, policy, infrastructure, stakeholders and development scenarios" ], "methods": [ "Requirements and interface coordination" ], "outputs": [ "Coordinated design requirements" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "beautifulsoup4", "crawl4ai", "matplotlib", "numpy", "pandas", "pandoc", "python-docx", "scipy", "trafilatura" ], "required_skills": [ "skill-web-research", "skill-data-analysis", "skill-business-writing" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-urban-planner/professional.json", "source_id": "prof-urban-planner", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "aa2f0f9a4499d53049be73209597e34bda44dd0538f6499bf58361173e7db91d", "role_sha256": "e8f51af9f288880ebb74bda4fed9ab319be37abd5c2c727ee1740e955f88092b", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-ux-researcher", "name": "UX Researcher", "description": "Qual + quant research: interviews, usability, surveys, analytics", "category": "product", "category_name": "Product", "family": "business", "family_name": "Business operations", "adaptation_state": "described", "tasks": [ "Qual + quant research: interviews, usability, surveys, analytics" ], "methods": [ "User research, prioritization and prototyping" ], "outputs": [ "Requirements, prototype or research findings" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "matplotlib", "numpy", "pandas", "scipy" ], "required_skills": [ "skill-data-analysis" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-ux-researcher/professional.json", "source_id": "prof-ux-researcher", "source_version": "1.4.1", "source_lifecycle": "published", "manifest_sha256": "0de32f65fe259e8def19f28586b90cefc72f6c580c4ce6f79be20bfd3d755fc7", "role_sha256": "c6b3ae4f5ac9f2d83508cd21470c3c715776cb3ea00bd72527d8586f85ba7155", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "notion", "fetch", "sqlite" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-validator-operator", "name": "Validator Operator (PoS chains)", "description": "Run Ethereum / Solana / Cosmos validators — uptime, slashing avoidance, MEV-boost, key custody, governance", "category": "infra", "category_name": "Infrastructure", "family": "technology", "family_name": "Technology", "adaptation_state": "described", "tasks": [ "Run Ethereum / Solana / Cosmos validators — uptime, slashing avoidance, MEV-boost, key custody, governance" ], "methods": [ "Change planning, monitoring and recovery review" ], "outputs": [ "Change plan or operational report" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "curl", "git", "jq" ], "required_skills": [ "skill-linux-sysadmin", "skill-monitoring-observability" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-validator-operator/professional.json", "source_id": "prof-validator-operator", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "fd4a3dc168358cea83106937ce4e6aea531798acc1f9f8d578a9f217eebdba85", "role_sha256": "b5a439e9130aa4f8a9af10b487cfa2ced82dcb2de7927930e178a1cd94347049", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-video-producer", "name": "Video Producer (concept to published video, scripts, editing, distribution)", "description": "Produces video from idea to publication: concepts and scripts, storyboards, recording and generation plans, editing and post-production direction, captions and formats per channel, and release with performance follow-up", "category": "content", "category_name": "Content", "family": "research-media", "family_name": "Research and media", "adaptation_state": "described", "tasks": [ "Produces video from idea to publication: concepts and scripts, storyboards, recording and generation plans, editing and post-production direction, captions and formats per channel, and release with performance follow-up" ], "methods": [ "Source review and editorial iteration" ], "outputs": [ "Reviewable publication draft" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "Pillow", "ffmpeg", "ffmpeg-python", "moviepy" ], "required_skills": [ "skill-content-writing", "skill-business-writing", "skill-project-controls" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-video-producer/professional.json", "source_id": "prof-video-producer", "source_version": "1.0.0", "source_lifecycle": "published", "manifest_sha256": "f2f93c88fe8ec6af76b30998b29e4ee3f08a87efa4bd6d87849fbf6bce0f2be4", "role_sha256": "18e456b8b47b7fa367d41a5780742501a862db02d59ea3eef8c4604a1cec18d9", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem", "fetch" ], "optional": [] } }, "related_scenarios": [] }, { "id": "prof-warehouse-operations-manager", "name": "Warehouse Operations Manager", "description": "Runs safe receiving, storage, inventory accuracy, picking, dispatch and labour capacity", "category": "logistics", "category_name": "Logistics", "family": "supply-chain", "family_name": "Supply chains", "adaptation_state": "described", "tasks": [ "Runs safe receiving, storage, inventory accuracy, picking, dispatch and labour capacity" ], "methods": [ "Constraint-based planning and delivery tracking" ], "outputs": [ "Transport or warehouse plan" ], "guidance_basis": "Editorial starting points for adaptation, not observed task results.", "tools": [ "matplotlib", "numpy", "openpyxl", "pandas", "pandoc", "python-docx", "scipy", "statsmodels" ], "required_skills": [ "skill-demand-supply-planning", "skill-quality-management", "skill-ehs-management", "skill-data-analysis" ], "owner_contact": "Escalate missing inputs, unclear authority, failed criteria or irreversible external actions.", "source": { "archive": "universal-professional-drones-production-20261015.tar.gz", "manifest_path": "UNIVERSAL/professionals/prof-warehouse-operations-manager/professional.json", "source_id": "prof-warehouse-operations-manager", "source_version": "1.4.0", "source_lifecycle": "published", "manifest_sha256": "b360c57d8b3210a96d7eb270c0c7f3821205cd89ffa9fb34f1dab5e1c4390fe4", "role_sha256": "7b6aad8eb16e8608c557a8306a630741ed4606efed7b9dc338fa7af0899b1368", "readiness_sha256": "998efc59fa83cc0bb0599da164c3b7ec77d992cf10624990303f3536b0be0f5e", "role_integrity_matches_manifest": true }, "adaptation_dependencies": { "source_platform": "UNIVERSAL", "base_image": "universal-v2-agentic-mega-gold", "auth_modes": [ "vault-native", "llm-gateway" ], "mcp": { "required": [ "service-bridge", "memory", "sequential-thinking", "time", "filesystem" ], "optional": [] } }, "related_scenarios": [] } ] }