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Found 52 Skills
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.
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".
Create or update living documentation from git history (branch diff, current branch, PR, or last N commits) for microservices. Use when users ask to document a feature/funcionalidad, document current branch/branch actual, generate release notes/changelog, explain what changed, or update docs for react, integrator, magento, or all services. Produces docs in each repo's docs/ folder (components, changelogs, adrs, runbooks, guides, technical, bugs, plans, tasks) with traceability to commits/files and Obsidian-compatible frontmatter.
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. Also use when the user wants to break a feature into tasks, plan before coding, track implementation progress, set up a new project structure, or organize work into specs and plans. Triggers on "map codebase", "initialize", "initialize project", "create feature", "plan", "tasks", "implement", "validate", "archive", "break this into tasks", "plan this feature", "start a new project".
Comprehensive code review with parallel specialist sub-agents. Analyzes requirements traceability, code quality, security, performance, accessibility, test coverage, and technical debt. Produces detailed findings and calls /qa-gate for final gate decision.
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.
Add ADR references to code for traceability. TRIGGERS - ADR traceability, code reference, document decision in code.
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.
Reviews a reverse-skill case package for scope readiness, Evidence to Finding to Path traceability, work item coverage, timeline references, and optional artifact hash integrity before report handoff.
Extracts technical API constraints from OpenAPI/Swagger specs and developer docs into a contract-ready API Access & Constraints Schedule with source traceability, risk flags, and change-control language. Use when drafting legal exhibits or schedules covering API access scope, rate limits, authentication, data fields, or deprecation terms for MSAs, SOWs, or order forms.
Used in Git development when you need to abandon current attempts and roll back to a historical commit. It automatically archives the current state to the archive/ branch and establishes bidirectional links (source and target) in ARCHIVE.md to ensure traceability of the development decision flow. Suitable for scenarios requiring safe rollback while retaining the context of failed attempts.
AI SDLC reusable quality-lens workflow. Use when an AI assistant needs to challenge a requirement, design, plan, test strategy, change, or delivery artifact through pre-mortem, adversarial, edge-case, stakeholder-conflict, reversibility, abuse-case, operational-failure, or assumption lenses and finalize evidence-backed findings with ownership and traceability. Supports `--quick-flow` for selected high-value lenses and `--full-flow` for the complete applicable registry.