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my-ai-tools
my-ai-tools には jellydn から収集した 42 個の skills があり、リポジトリ単位の職業カバレッジとサイト内 skill 詳細ページを表示します。
このリポジトリの skills
Verify understanding after implementation with targeted quizzes
Clarify requirements through targeted questions — uncovers unknown unknowns in specs
Remove AI-generated code patterns that don't match codebase style
Review code for quality, security, and best practices — read-only analysis
Create clear documentation for code and APIs
Audit code for security vulnerabilities — read-only analysis
Generate comprehensive tests for code changes
Remove AI-generated code patterns that don't match codebase style
Review code for quality, security, and best practices — read-only analysis
Create clear documentation for code and APIs
Audit code for security vulnerabilities — read-only analysis
Generate comprehensive tests for code changes
Remove AI-generated code patterns that don't match codebase style
Review code for quality, security, and best practices — read-only analysis
Create clear documentation for code and APIs
Audit code for security vulnerabilities — read-only analysis
Generate comprehensive tests for code changes
Find unknown unknowns before starting implementation — searches git history, patterns, and architecture for hidden gotchas
Experiment with model capabilities — HTML reports, embedded questionnaires, proactive research, multi-step reasoning
Map codebase structure with parallel analysis — produces 7 documents about architecture, concerns, and conventions
Discover context using MCP tools — fff, sem, ctx, qmd, codebase-memory-mcp for codebase understanding
Search project documentation — ADRs, wiki entries, conventions via ripgrep, qmd, fff, and ctx
Search git history for context — commit messages, blame, related changes, impact analysis
Create handoff plans for continuing work across sessions
Log implementation decisions — tracks deviations from plan and captures rationale
Resume work from previous handoff sessions stored in .planning/handoffs/
Turn ideas into executable goal packages with guided interviews and codebase analysis
Replace port numbers with stable named .localhost URLs for local development
Manage project knowledge with qmd — captures learnings, decisions, and conventions
Remove AI-generated code slop from git diffs to maintain code quality
Run an extremely strict maintainability and structural code quality review — flags abstraction issues, spaghetti growth, and boundary leaks
Review the diff since a fixed point along two axes — Conventions (does the code follow this repo's coding standards and Tidy First practices?) and Intent (does the change do what it claims to do?). Runs both reviews in parallel sub-agents and reports them side by side. Use when you want to review a branch, a PR, work-in-progress changes, or ask to "review since X".
Update docs when code changes — reviews commits and syncs user-facing documentation
Draft pull requests with structured descriptions using gh CLI
Convert PRDs to prd.json format for the Ralph autonomous agent system
Record architecture decisions with ADRs — captures why, alternatives considered, and consequences
Group staged changes into atomic commits with commitizen convention
Build a persistent compounding wiki from raw sources using the LLM Wiki pattern
Fix PR review comments by implementing requested changes
Generate Product Requirements Documents from feature ideas — plans specs and requirements