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Expert Python development focusing on clean code, comprehensive testing, performance optimization, and best practices with detailed documentation

Assist with core product management activities including writing PRDs, analyzing features, synthesizing user research, planning roadmaps, and communicating product decisions. Use when you need help with PM documentation, analysis, or planning workflows that integrate with your codebase.

Format documentation with emojis, status bars, and versioning matrix. Use when creating or updating README files, documentation, specs, or any markdown files.

企画・設計・アイデア出し・ブレインストーミング・要件定義など、プロジェクトの企画フェーズに関する会話をしているときに自動発動。会話の内容を自動的にdocs/ディレクトリにタイムスタンプ付きドキュメントとして保存する。

Generate API documentation in OpenAPI/Swagger, Markdown, or Postman Collection formats. Use when documenting REST APIs, GraphQL schemas, or creating client code examples.

Creates technical documentation including READMEs, API references, user guides, architecture docs, ADRs, and runbooks. Use for requests to create, write, generate, or draft documentation. Trigger phrases include "document this", "write docs", "create readme", "API reference", "user guide", "architecture docs", "ADR", "runbook". For updating existing READMEs, use updating-readme instead.

TDD（テスト駆動開発）に基づいたテストコード作成スキル。Red-Green-Refactorサイクルを実践し、 t-wadaのベストプラクティスに従ってテストファーストで高品質なテストを作成します。 Backend（Go test）とFrontend（Jest）の両方に対応。

This skill should be used when the user asks about "Zenn記法", "Zenn Markdown", "メッセージブロック", "アコーディオン", "埋め込み", "Zenn特有の記法", or mentions writing Zenn articles with specific formatting needs. Provides comprehensive knowledge of Zenn-specific Markdown syntax and best practices.

Comprehensive code analysis for architecture, performance, security, and quality using PAL MCP. Use when reviewing codebases, assessing technical decisions, or planning improvements. Triggers on analysis requests, architecture reviews, or code quality assessments.

Interactive prompt builder for creating high-quality deep research prompts through adaptive interviewing. Use when users need to transform a basic research topic into a comprehensive, well-structured research prompt optimized for deep analysis. Helps build research prompts from vague ideas, enhance existing questions with best practices, and create structured prompts for any domain including product comparisons, technical documentation, academic literature, and market analysis.

Production-ready starter project for React + Cloudflare Workers + Hono with core services(D1, KV, R2, Workers AI) and optional advanced features (Clerk Auth, AI Chat, Queues, Vectorize).Complete with planning docs, session handoff protocol, and enable scripts for opt-in features.Use when: starting new full-stack project, creating Cloudflare app, scaffolding web app,AI-powered application, chat interface, RAG application, need complete starter, avoid setup time,production-ready template, full-stack boilerplate, React Cloudflare starter.Prevents: service configuration errors, binding setup mistakes, frontend-backend connection issues,CORS errors, auth integration problems, AI SDK setup confusion, missing planning docs,incomplete project structure, hours of initial setup.Keywords: cloudflare scaffold, full-stack starter, react cloudflare, hono template, production boilerplate,AI SDK integration, workers AI, complete starter project, D1 KV R2 setup, web app template,chat application scaffold, RAG st

Query DeepWiki for repository documentation and structure. Use to understand open source projects, find API docs, and explore codebases.

Manage and query the documentation dependency index. Use this to identify which documents need to be updated when code changes.

Create world-class, production-grade technical documentation with exceptional clarity and precision. Use this skill when the user asks to write READMEs, API references, guides, or code comments. Generates professional, accessible content that rivals top-tier tech companies.

Provides ASSERT/ASSUME macro pattern, .sby file template, and f_past_valid usage. Triggers when adding formal verification or writing assertions.

Use when receiving code review feedback, before implementing suggestions, especially if feedback seems unclear or technically questionable - requires technical rigor and verification, not performative agreement or blind implementation

API design patterns for REST, GraphQL, and gRPC. Use when designing API endpoints, creating OpenAPI specs, implementing GraphQL schemas, or building gRPC services.

Build TM Forum (TMF) MCP servers from TMF OpenAPI specs (TMF6xx/7xx YAML). Use when you are given a TMF OpenAPI file and asked to (1) implement an MCP server exposing TMF operations as tools, (2) generate a mock TMF API server + client + MCP layer, or (3) standardize tool naming, create/update inputs, $ref/allOf handling, and /hub event-subscription patterns for TMF APIs.

Spawn and manage Claude sub-agents for parallel or delegated tasks. WHEN: User needs parallel operations, multi-step autonomous research, or wants to delegate complex tasks to sub-agents. Use when task can be parallelized or requires independent exploration. WHEN NOT: Simple single-step operations, sequential dependencies, specific file reads (use fs_read_file), writing code directly (do it yourself).

Use when working on Nuxt 4+ projects - provides server routes, file-based routing, middleware patterns, Nuxt-specific composables, and configuration with latest docs. Covers h3 v1 helpers (validation, WebSocket, SSE) and nitropack v2 patterns.