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Found 86 Skills
Optional AI SDLC evidence-council workflow. Use when an AI assistant needs to review a high-impact topic through several explicit perspectives, orchestrate simulated lenses or truly independent reviewer executions, and synthesize evidence-backed agreements, conflicts, proposals, owners, and unresolved questions without allowing panel members to rewrite authoritative artifacts. Supports `--quick-flow` for labeled simulated review and `--full-flow` for stricter panel and evidence coverage.
AI SDLC package trust and privacy-preserving local metrics workflow. Use when an AI assistant needs to verify package origin, file integrity, harness compatibility, declared capabilities, provenance evidence, or generate reproducible aggregate run, retry, budget, coverage, and freshness metrics without collecting source, prompts, commands, or diffs. Supports `--quick-flow` and `--full-flow`.
Threat modeling methodologies (STRIDE, DREAD), attack trees, threat modeling as code, and integration with SDLC for proactive security design
AI SDLC code review workflow. Use when an AI assistant is asked to review a diff, PR, branch, commit, staged changes, or completed implementation against SDD requirements, tests, API contracts, security, and scope discipline. Supports `--quick-flow` for fast assumption-driven execution and `--full-flow` for question-driven verified execution.
AI SDLC security testing workflow. Use when an AI assistant is asked for OWASP review, security testing, abuse-case analysis, authz/authn review, input validation review, secret exposure review, or security-focused validation of a diff, endpoint, workflow, or subsystem. Supports `--quick-flow` for fast assumption-driven execution and `--full-flow` for question-driven verified execution.
Use when working on the spec branch of sdlc-dev, when requirements are ambiguous, scope is unstable, constraints are unclear, and issues such as context drift, unfounded assumptions, multiple questions asked at once, or requests to skip the FEATURE_DIR/raw gate occur.
Optional AI SDLC research workflow. Use when an AI assistant needs to investigate a customer, market, domain, technology, regulation, competitor, operational question, or implementation uncertainty and produce a routed source inventory plus synthesized findings with confidence, limitations, open questions, and delivery trace targets. Supports `--quick-flow` for focused evidence and `--full-flow` for multi-source and source-diversity gates.
AI SDLC declarative workflow planning. Use when an AI assistant needs to validate a versioned workflow, plan typed dependency steps, evaluate bounded conditions, enforce approval gates, attach deterministic hooks, detect cycles, or create safe dependency waves with sequential fallback when host concurrency or isolation is unavailable. Supports `--quick-flow` and `--full-flow`.
Turns a product brief (its Scope and Key flows) or a spec's Phasing into a tracker backlog — epics, stories with acceptance criteria, tasks — with stable ids in titles, epic checklists, and Epic links, filing every issue through om-prepare-issue so dedupe, SDLC labels, and rationale come for free. Refuses a brief that is not ready; shows the whole tree and waits before writing. Use for "build the backlog", "turn the brief into issues".
Optional AI SDLC architecture workflow. Use when an AI assistant needs to define system boundaries, components, interfaces, architectural constraints, alternatives, decisions, tradeoffs, risks, or validation for a feature and produce routed human and machine artifacts linked to requirements and durable decisions. Supports `--quick-flow` for focused design and `--full-flow` for strict decision, risk, and validation coverage.
AI SDLC evidence-backed project context and bounded task-pack workflow. Use when an AI assistant needs to onboard to a repository, detect stack and commands, map ownership and test topology, check context drift, conditionally select task sources, exclude secrets, or allocate a freshness-aware context pack within an explicit token budget. Supports `--quick-flow` for focused evidence and `--full-flow` for stricter repository coverage.
Use when you need to execute R3 (Prototype Generation) in the product requirement Spec process of sdlc-dev, generate requirements/prototype.md based on requirements/prd.md (including task flow + page structure + ASCII wireframe + AC mapping + walkthrough script), and avoid proceeding with generation without context/PRD, using Open Questions instead of verification checklists, or using non-ASCII formats that make the prototype untraceable and unreviewable.