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Found 108 Skills
AI SDLC evidence-backed retrospective workflow. Use when delivery work is complete or paused and an AI assistant needs to capture observations, connect them to validation or artifact evidence, formulate reviewable process or policy improvement proposals, assign ownership, and preserve the rule that policy changes require an accepted decision. Supports `--quick-flow` for focused learning and `--full-flow` for strict evidence and decision gates.
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.
Use this when you need to execute R4 (generate an interactive Demo project based on requirements/prototype.md) in the sdlc-dev product requirement Spec process, and need to avoid skipping spec-context, proceeding when prototype.md is missing or the runnable Demo project root directory is missing, or creating custom pages/directories that lead to untraceability and inability to close the loop.
Used when a Spec Pack is completed, reusable assets need to be promoted to the project SSOT (ADR/contract/ops/NFR/registry), and there are risks of "contaminating the project with full package replication / skipping spec-context / mistaking merge-back for git merge".
Use when you need to generate or update `{FEATURE_DIR}/verification/usecase.md` (test cases) during the verification phase of the Spec Pack, and require AC traceability and a structure that supports automated script generation.
Create a living specification (Spec) or plan for a feature by analyzing requirements and codebase
Use when you need to generate or update `{FEATURE_DIR}/verification/suites.md` (test suite) during the verification phase of Spec Pack, organize test cases into executable sets and define blocking rules and execution order.
Use when you need to generate `{FEATURE_DIR}/verification/report-{date}-{version}.md` (test report) during the verification phase of Spec Pack, provide deliverable conclusions that are traceable to test cases and defect references.
Use this when the Discover (reverse engineering) of legacy projects tends to get out of control in coverage. You need to first conduct module classification (P0/P1/P2) and constrain the depth of reverse engineering, ensuring that high-ROI modules are made traceable first instead of "writing everything but making it unmaintainable."
AI-native software development lifecycle that replaces traditional SDLC. Triggers on "plan and build", "break this into tasks", "build this feature end-to-end", "sprint plan this", "superhuman this", or any multi-step development task. Decomposes work into dependency-graphed sub-tasks, executes in parallel waves with TDD verification, and tracks progress on a persistent board. Handles features, refactors, greenfield projects, and migrations.
Autonomous SDLC router. Takes a job, classifies complexity, executes the appropriate lev-* workflow (from trivial fix to full epic), and returns "done" with runnable instructions. One shot to full auto: spec/bd/poc/impl. Subagent returns completion artifact. Triggers: "sidequest", "side quest", "just do it", "autonomous", "one shot"
Launch Loki Mode autonomous SDLC agent. Handles PRD-to-deployment with minimal human intervention. Invoke for multi-phase development tasks, bug fixing campaigns, or full product builds.