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Found 40 Skills
When a GDD is revised, scans all ADRs and the traceability index to identify which architectural decisions are now potentially stale. Produces a change impact report and guides the user through resolution.
Validates completeness and consistency of the project architecture against all GDDs. Builds a traceability matrix mapping every GDD technical requirement to ADRs, identifies coverage gaps, detects cross-ADR conflicts, verifies engine compatibility consistency across all decisions, and produces a PASS/CONCERNS/FAIL verdict. The architecture equivalent of /design-review.
Complete Problem-Based Software Requirements Specification methodology following Gorski & Stadzisz research. Use when you need to perform requirements engineering from business problems to functional requirements with full traceability.
AI SDLC repository delivery-graph and evidence-freshness workflow. Use when an AI assistant needs to index lifecycle traceability, resolve end-to-end paths, report gaps or orphans, register evidence identity, propagate stale dependencies, or calculate fresh evidence coverage. Supports `--quick-flow` for deterministic local analysis and `--full-flow` for strict trace and evidence review.
AI SDLC commit preparation workflow. Use when an AI assistant is asked to commit repository changes, prepare an auditable commit message, stage files safely, include SDD traceability, verify branch/spec alignment, or verify the working tree before committing. Supports `--quick-flow` for fast assumption-driven execution and `--full-flow` for question-driven verified execution.
When the user wants to optimize medical device distribution, manage device traceability, handle consignment inventory, or ensure regulatory compliance for medical devices. Also use when the user mentions "medical device logistics," "UDI compliance," "device traceability," "consignment management," "implant tracking," "loaner sets," "FDA compliance," "sterile device distribution," "recall management," or "GS1 standards." For hospital internal logistics, see hospital-logistics. For pharmaceutical distribution, see pharmacy-supply-chain.
Analyze, prioritize, and document test cases in TMS (Jira/Xray) -- the bridge between manual QA and test automation. Use when creating Test/ATP/ATR artifacts, calculating ROI to choose which tests to automate, maintaining US-ATP-ATR-TC traceability, or repairing broken TMS links. Supports four scopes: module-driven (exhaustive module exploration), ticket-driven (QA-approved user story), bug-driven (regression TC for a closed bug), and ad-hoc/exploratory. Produces three outcomes per TC: Candidate (feeds test-automation), Manual (terminal), Deferred (terminal). Triggers on: document tests, create test cases in Jira/Xray, prioritize for automation, ROI analysis, which tests to automate, Candidate vs Manual, link ATP to ATR, fix TMS traceability, stage 4, turn this bug into a regression test. Do NOT use for writing test code (test-automation) or running suites (regression-testing).
Generate architectural wikis with source code traceability. Creates comprehensive documentation including architecture overviews, module docs, data flow diagrams, and interactive static sites. Use when asked to document a codebase, generate architecture docs, create a wiki, or explain how a project is structured.
Specification-driven development with structured phases: Initialize, Plan, Tasks, Implement+Validate. Creates structured feature specs with traceability to requirements. Use when: starting projects, planning features, implementing with verification, or tracking decisions across sessions. Triggers on "map codebase", "initialize", "initialize project", "create feature", "plan", "tasks", "implement", "validate", "archive".
Parse ebooks, extract concepts and entities with citation traceability, classify by type/layer, and synthesize across book collections.
Comprehensive project planning and documentation generator for software projects. Creates structured requirements documents, system design documents, and task breakdown plans with implementation tracking. Use when starting a new project, defining specifications, creating technical designs, or breaking down complex systems into implementable tasks. Supports user story format, acceptance criteria, component design, API specifications, and hierarchical task decomposition with requirement traceability.
Analyze codebase structure for reverse engineering. Identify entry points, dependencies, modules, and components with file:line traceability. Creates manifest.json for pipeline chaining with Phase 2 (logic visualization). Language-agnostic with optional language reference files. Use when: reverse engineer, analyze structure, structure analysis, codebase analysis, re-structure-analysis.