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Found 194 Skills
Use when a skill, plan, or rule file needs a frozen Starlark governance rule block generated, or an existing frozen block drift-checked against a candidate. Invoke explicitly — not for general rule discussion.
Design and manage reference data systems — security master, client master, account master, identifier mapping, pricing data, and governance. Use when building or evaluating a security master database, mapping identifiers across systems (CUSIP to ISIN, SEDOL to FIGI), designing client master models for onboarding or KYC, defining account master attributes across custodians, implementing pricing validation with vendor hierarchy, establishing reference data governance and stewardship, handling identifier changes from corporate actions, or troubleshooting data quality issues traced to stale prices or missing identifiers. Trigger on: security master, CUSIP, ISIN, SEDOL, FIGI, client master, account master, pricing data, reference data, golden source, MDM, master data, identifier mapping, data governance, pricing validation.
The comprehensive Celo ecosystem skill. Ecosystem intelligence, builder tools, DeFi protocol reference, MiniPay development, AI agent infrastructure, governance, grants, and verified contract addresses — all in one skill. Powered by The Grid for live cross-chain ecosystem data.
Implements knowledge graphs for AI-enhanced relational knowledge. Covers ontology design, graph database selection (Neo4j, Neptune, ArangoDB, TigerGraph), entity extraction, hybrid graph-vector architecture, query patterns, and AI integration. Use when implementing knowledge graphs, designing ontologies, extracting entities and relationships, selecting a graph database, or building hybrid graph-vector search. Use for knowledge graph, ontology design, entity resolution, graph RAG, hallucination detection. For architecture selection and governance, use the knowledge-base-manager skill. For document retrieval pipelines, use the rag-implementer skill.
Trae-optimized PUA high-agency governance skill for npx skills installation. Only activate it in scenarios such as explicit PUA requests, repeated task failures, user frustration, giving-up/passive behavior, or unverified task completion. Do not trigger it for normal first-attempt tasks.
Build or audit a design system including component library, design tokens, naming conventions, contribution model, and documentation. Use this skill whenever the user wants to build a design system, audit an existing system, define design tokens at the system level, structure a component library, or set up design system governance. Triggers on design system, component library, design tokens, atomic design, atoms, molecules, organisms, design system documentation, Storybook, Figma library, system governance, design contribution model. Also triggers when teams are inconsistent across products and a system is the answer.
Retrieve ESG ratings and scores using Octagon MCP. Use when analyzing Environmental, Social, and Governance ratings, MSCI ESG ratings, Sustainalytics risk ratings, industry ESG rankings, and sustainability metrics for any public company.
Chief AI Officer advisory for startups: model build-vs-buy decisions (API vs fine-tune vs in-house), AI risk classification under EU AI Act + US state patchwork, AI cost economics (API-to-self-hosted breakeven), and AI team org evolution. Use when deciding whether to call an API or fine-tune, classifying AI use cases for regulatory risk, calculating when self-hosting pays off, sequencing AI hires, or when user mentions CAIO, AI strategy, model selection, foundation model, fine-tuning, EU AI Act, NIST AI RMF, AI governance, model risk, or AI economics. Strategic only — does not duplicate engineering AI/ML skills.
Design enterprise-grade agent systems with Microsoft's agent framework patterns: role separation, workflow control, policy boundaries, and observability. Use when users need robust organizational agent workflows, governance, and maintainable multi-agent architecture.
Guides edge and tactical autonomous systems—perception-planning-control under latency and safety constraints; behavior trees/state machines vs learned policies; human-on-the-loop; geofencing, no-strike rules, mission abort; sim and field testing; ROS2/middleware patterns; sensor fusion; degraded modes; autonomy audit logging. Use for UAS/autonomous stacks, safety rules, HITL, sim-to-field validation, fail-safe—not LLM products (ai-engineer), LLM red team (ai-redteam), safeguard serving (ml-infrastructure-engineer-safeguards), governance only (ai-risk-governance), MCU firmware without autonomy (embedded-real-time-software-engineer), plant PLC/DCS (control-software-developer), HIL security bench (hardware-in-the-loop-security-tester).
Guides end-to-end lifecycle governance for mission-critical, high-assurance, or zero-failure- tolerance systems—concept through retirement: phases, gates, evidence, traceability, obsolescence, tech refresh, configuration baselines, NDA-safe regulated/classified patterns, assurance/DevSecOps/ ATO interfaces, decommissioning and data disposition. Use for extreme lifecycle, system lifecycle, mission-critical lifecycle, lifecycle gates, sustainment, tech refresh, obsolescence management, decommissioning, configuration baseline, lifecycle evidence, end-to-end lifecycle, or retire a system—not TPM-only (technical-program-manager), HRO-only (zero-tolerance-for-failure), tiering-only (mission-critical), classified pipeline-only (classified-software-devsecops-engineer), formal proofs (software-assurance-formal-methods-specialist), compliance-only (compliance-engineer), CI-only (build-validator), infra portfolio-only (vp-of-infrastructure).
Guides cleaning and standardizing tabular datasets before analysis, modeling, or reporting—profiling, quality rules, missing values, duplicates, outliers, type coercion, encoding fixes, record linkage, deduplication, high-level PII handling (not legal advice), actuarial/insurance field scrubbing, reproducible scrub pipelines, validation checks, and sign-off. Distinct from warehouse ETL or statistical modeling. Use when the user asks for "data scrubbing", "clean this dataset", "scrub the data", "data cleaning", "dedupe records", "handle missing values", "outlier treatment", "standardize columns", "data quality rules", "profile this table", or "prepare data for modeling". Not warehouse pipelines (data-warehouse-engineer), ML modeling (data-scientist, actuary), privacy programs (compliance-engineer), FinOps only (finops-analyst), or assumption governance (assumption-setting).