ccplugins

Skill for creating parallel development plans with multiple developers. Leverages git worktree for branch strategy, task dependency analysis, critical path calculation, developer role assignment, and timeline creation. Use for requests like "create a parallel development plan", "I want to develop with multiple people simultaneously", "divide work with worktree", or "maximize development parallelization". Also supports on-demand parallel tasks for quick fixes with requests like "fix XX in parallel", "do YY with worktree", or "add parallel task".

複数開発者での並列開発計画書を作成するスキル。git worktree を活用したブランチ戦略、タスクの依存関係分析、クリティカルパス計算、開発者ロール割り当て、タイムライン作成を行う。「並列開発計画を作って」「複数人で同時開発したい」「worktree で分担したい」「開発を最大限並列化したい」などのリクエスト時に使用。また、「〇〇を並列で修正して」「worktree で△△をやって」「並列タスクを追加」などのリクエストで、オンデマンドの並列タスクを即座に開始できる。

Use for all blog writing tasks including creating articles (Zenn Japanese, dev.to/Medium English), managing ideas, and setting up blog projects. This is the unified entry point for technical blog writing workflow. Supports idea tracking with status management (backlog/in-progress/done).

Use when you need to fine-tune(ファインチューニング) and optimize LangGraph applications based on evaluation criteria. This skill performs iterative prompt optimization for LangGraph nodes without changing the graph structure.

Analyze LangGraph application architecture, identify bottlenecks, and propose multiple improvement strategies

MANDATORY specification writing skill. ONLY way to create/update specs. Auto-invoke when: - Creating specs: New projects, features ("I want to create XX") - Updating specs: Feature additions, requirement changes, architecture updates - Syncing specs: Major code changes (3+ files), refactoring, session end - Keywords: specifications/spec/design/architecture/requirements/PRD Outputs to .spec-manager/. Critical rules and workflow details in skill body.

Use when specifying or implementing LangGraph applications - from architecture planning and specification writing to actual code implementation. Also use for designing agent workflows or learning LangGraph patterns. This is a comprehensive guide for building AI agents with LangGraph, covering core concepts, architecture patterns, memory management, tool integration, and advanced features.