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Found 159 Skills
Systematically analyze codebase structure, complexity, dependencies, and architectural patterns to understand project organization
Discover patterns, rules, and interfaces through iterative analysis cycles. Use when analyzing business rules, technical patterns, security, performance, integration points, or domain-specific areas. Includes cycle pattern for discovery to documentation to review workflow.
Invoke IMMEDIATELY via python script when user requests codebase understanding, architecture comprehension, or repository orientation. Do NOT explore first - the script orchestrates exploration.
Set up your project's global rules, a lean and well-structured root CLAUDE.md (plus a starter .claude/), following the course methodology. Greenfield: pass your PRD and/or architecture-spec path and it derives rules from your engineering decisions (a PRD alone is product context). Brownfield: leave it blank to derive from your primed codebase (run /prime-codebase first), or pass a codebase-analysis doc for a large repo. Use when initializing or re-deriving the AI Layer's rules, onboarding a codebase, or replacing a generic /init output. The customizable replacement for /init.
Use this skill when user wants to create a refactor plan.
Survey a codebase's animation and motion code as a senior motion advisor, then produce a prioritized audit and self-contained implementation plans for other agents (or cheaper models) to execute. Read-only on source code — it plans improvements, it does not apply them. Use when the user asks to "improve the animations", "audit the motion", "make this app feel better", or wants a roadmap of animation fixes rather than a review of a single diff.
Analyzes existing codebases to understand structure, patterns, and technical debt
Build a multi-page Markdown wiki directory for a large software repository after reading and analyzing the whole codebase. Use when the agent is asked to create repository wiki documentation, onboarding docs, architecture guides, codebase tours, maintainer handbooks, or deep explanations of modules, core code paths, algorithms, design decisions, tradeoffs, tests, tooling, and operations for code learners or new maintainers. Optimized for large repositories with hundreds of thousands of lines of code where maintainers need broad coverage and deep subsystem documentation. Also supports optional Rspress/static documentation site setup when the user explicitly asks to publish or deploy the generated wiki. Supports Markdown output with Mermaid, Graphviz, and KaTeX where useful.
When the user wants a comprehensive technical analysis of a codebase or project. Also use when the user mentions 'analyze this codebase,' 'technical overview,' 'document this architecture,' 'what does this codebase do,' 'summarize this repo,' 'code audit,' 'architecture review,' 'codebase walkthrough,' or 'analyze this project.' Performs a multi-phase analysis covering architecture, code quality, testing, and infrastructure, producing a detailed markdown report targeting engineers. For quick code searches or single-file reviews, see standard editor tools.
Plan a multi-file refactor with proper sequencing and rollback steps
Reverse-engineer any codebase into a complete Product Requirements Document (PRD). Analyzes routes, components, state management, API integrations, and user interactions to produce business-readable documentation detailed enough for engineers or AI agents to fully reconstruct every page and endpoint. Works with frontend frameworks (React, Vue, Angular, Svelte, Next.js, Nuxt), backend frameworks (NestJS, Django, Express, FastAPI), and fullstack applications. Trigger when users mention: generate PRD, reverse-engineer requirements, code to documentation, extract product specs from code, document page logic, analyze page fields and interactions, create a functional inventory, write requirements from an existing codebase, document API endpoints, or analyze backend routes.
Deep codebase analysis to generate 8 comprehensive documentation files. Adapts based on path choice - Greenfield extracts business logic only (tech-agnostic), Brownfield extracts business logic + technical implementation (tech-prescriptive). This is Step 2 of 6 in the reverse engineering process.