Loading...
Loading...
Found 114 Skills
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.
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.
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.
Wield Google's Gemini CLI as a powerful auxiliary tool for code generation, review, analysis, and web research. Use when tasks benefit from a second AI perspective, current web information via Google Search, codebase architecture analysis, or parallel code generation. Also use when user explicitly requests Gemini operations.
Writes detailed video scripts for Remotion based on input requirements and codebase analysis
Generate a concise overview of the current project — structure, purpose, recent activity, and open questions. Use when the user asks "what is this repo?", "give me an overview", or "what's going on in this project?".
Legacy-project style inheritance skill. Use when the user types /inherit-legacy-style, or when onboarding an AI coding agent onto a hand-written legacy project and you need to prevent "style drift" (the model imposing its pretrained mainstream idioms onto the project). Language- and framework-agnostic — it aligns meta-architecture only, not syntax. Once run, it becomes a behavioral constraint on all subsequent coding tasks. Do NOT use for pure research or one-off questions unrelated to code-style alignment.
Extract project-specific coding rules and domain knowledge from existing codebase, generating markdown documentation for AI agents.
Technical due diligence for M&A, investment, or acquisition. Reads a target company's codebase and generates a comprehensive tech DD report with architecture assessment, tech debt quantification, scalability analysis, security posture, team capability inference, build system quality, test coverage, deployment maturity, and open source license risks. Outputs tech-dd-report.md formatted like a real investment memo with risk ratings, remediation costs, and go/no-go recommendation.