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Found 29 Skills
CQRS and Event Sourcing for auditability, read/write separation, and temporal queries. Triggers: CQRS, event-sourcing, audit-trail, temporal queries, distributed-systems Use when: read/write scaling differs or audit trail required DO NOT use when: selecting paradigms (use architecture-paradigms first), simple CRUD without audit needs.
Rigor Improve implementation leaf skill for auditable candidate implementation in deep learning research repositories. Use when the researcher explicitly authorizes exploratory work on an isolated branch or worktree to transplant modules, adapt a backbone, add LoRA or adapter layers, replace a head, or stitch together meaningful low-risk migration ideas with rollback-aware records in `explore_outputs/`. Do not use for end-to-end exploration orchestration on top of `current_research`, trusted baseline reproduction, conservative debugging, environment setup, verified contribution claims, or default repository analysis.
Design an auditable playbook when no narrower one fits: a large migration, an ambitious multi-part change, or work a human reviews after stepping away. Scales rigor to the task, runs a hypothesis loop, and logs decisions via show-me-your-work. Use for /figure-it-out, 'figure it out', a large migration, or when no narrower playbook applies.
Keep a reviewable decision trail for long-running or unattended work: a TSV log with one row per decision (what, why, evidence, result). Local by default; commit it when a reviewer needs the trail to trust the result. Use for /show-me-your-work, autonomous or multi-phase runs, or work a human reviews after stepping away.
Protected Health Information (PHI) and Personally Identifiable Information (PII) compliance patterns for healthcare applications. Covers data classification, access control, audit trails, encryption, and common leak vectors.
Structures the human review experience for factory-mode builds. Audit trail summaries, PR digests, retrospective synthesis, quality trend tracking, and autonomy tuning interface. Activate during Phase 3 human review.
Automatic risk assessment before every critical action in agentic workflows. Detects irreversible operations (file deletion, database writes, deployments, payments), classifies risk level, and requires confirmation before proceeding. Triggers on destructive keywords like deploy, delete, send, publish, update database, process payment.
Patterns and techniques for adding governance, safety, and trust controls to AI agent systems. Use this skill when: - Building AI agents that call external tools (APIs, databases, file systems) - Implementing policy-based access controls for agent tool usage - Adding semantic intent classification to detect dangerous prompts - Creating trust scoring systems for multi-agent workflows - Building audit trails for agent actions and decisions - Enforcing rate limits, content filters, or tool restrictions on agents - Working with any agent framework (PydanticAI, CrewAI, OpenAI Agents, LangChain, AutoGen)
AI generation provenance and audit trail tracking. Records decision factors, data lineage, reasoning chains, confidence scoring, and cost tracking for AI-generated content.
Manage project state using append-only, time-based Markdown files under /project/. Use when managing multi-epic projects, tracking decisions over time, maintaining audit trails, coordinating distributed teams, or requiring rollback visibility. Forces context loading, explicit confirmation gates, and immutable history preservation.
Use when implementing draft/publish workflows, version history, content rollback, or audit trails. Covers versioning strategies, snapshot storage, diff generation, and version comparison APIs for headless CMS.
Sync delta specs to main specs and archive a completed change. Trigger: When the orchestrator launches you to archive a change after implementation and verification.