Expert in designing and building autonomous AI agents. Masters tool use, memory systems, planning strategies, and multi-agent orchestration. Use when: build agent, AI agent, autonomous agent, tool use, function calling.
Create, update, and comment on GitHub pull requests with focus on material impact, safety, and human reviewability
MCP Agent Mail - mail-like coordination layer for coding agents with memorable identities, inbox/outbox, searchable threads, advisory file reservations, pre-commit guards, and human-auditable Git artifacts. The backbone of multi-agent workflows.
実装完了後のテスト、lint、ベストプラクティスレビューを自動実行するスキル。 以下の状況で使用: (1) ユーザーが「実装完了」「完了」「できた」「終わった」「実装した」などと発言した時 (2) ユーザーが明示的に「/post-impl-validator」を実行した時 (3) ファイル編集後に「コミットして」「PRを作成」などと依頼された時
Manage specification documents in .agent/specs/. Use when user provides requirements, acceptance criteria, or feature descriptions that need to be tracked and validated against implementation.
Browser automation using Playwright MCP. Navigate websites, fill forms, click elements, take screenshots, and extract data. Use when tasks require web browsing, form submission, web scraping, UI testing, or any browser interaction.
Use the ClawdHub CLI to search, install, update, and publish agent skills from clawdhub.com. Use when you need to fetch new skills on the fly, sync installed skills to latest or a specific version, or publish new/updated skill folders with the npm-installed clawdhub CLI.
Generate specialized skills for each subsystem in the monorepo. Creates shared language skills and subsystem-specific checklists for high-quality AI code generation.
Maintain .agent state files. Use at session start, after meaningful steps, and before concluding: read/update constitution/memory/focus/issues/baseline consistently.
Docker image reviews, optimization, and step-building guidance. Analyzes Dockerfiles for best practices, security issues, and anti-patterns.
Deterministic router for math cognitive stack - maps user intent to exact CLI commands
Technology architecture specialist providing friendly coaching and system design guidance. Use when discussing system architecture, technology stack selection, design patterns, scalability, performance optimization, or integration strategies. Triggered by terms like "architecture", "design system", "tech stack", "scalability", "microservices", "database design", or "api design".
Problem-solving strategies for eigenvalues in linear algebra
Conduct structured interviews with the user. Use when multiple decisions need user input: ask ONE question at a time, wait for response, record answer, then proceed to next question.
Compare OpenAI Codex GPT-5.2 and code-searcher responses for comprehensive dual-AI code analysis. Use when you need multiple AI perspectives on code questions.
Real-time observability dashboard for multi-agent Claude Code sessions. Visualize agent interactions, tool usage, and session flows in real-time through a web dashboard. Track multiple agents running in parallel with swim lane visualization, event filtering, and live charts. USE WHEN user says 'start observability', 'agent dashboard', 'monitor agents', 'watch agent activity', 'multi-agent monitoring', 'track subagents', or needs to debug multi-agent workflows. **Key Features:** - 🔴 Real-time event streaming via WebSocket - 📊 Agent swim lanes showing parallel execution - 🔍 Event filtering by agent, session, event type - 📈 Live charts for tool usage patterns - 💾 Filesystem-based (no database required) **Inspired by [@indydevdan](https://github.com/indydevdan)**'s work on multi-agent observability. **Our approach:** Filesystem + in-memory streaming vs. indydevdan's SQLite database approach.
Use when configuring Dialyzer for Erlang/Elixir type checking and static analysis.
Use when implementing complex multi-step tasks, fixing critical bugs, or when quality and completeness matter more than speed - ensures comprehensive implementation without shortcuts through systematic analysis, implementation, and verification phases
Build defensible DCF models with cited sources, Excel export, and sensitivity analysis
LangGraph development for stateful multi-agent applications, cyclic workflows, conditional routing, human-in-the-loop patterns, and persistent state management. Use for complex AI orchestration, agent coordination, and production-grade agentic systems.