Wire Commands, Agents, and Skills together for complex features. Use when building features that need research, planning, and implementation phases.
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See how to installReview the instructions the agent will receive before you install.
Build features through structured phases with validation gates.
/develop <feature>
│
├── Phase 1: Research (orchestrator agent)
│ └── Score confidence → GO/HOLD
│
├── Phase 2: Plan (orchestrator agent)
│ └── Present plan → wait for approval
│
├── Phase 3: Implement (orchestrator agent)
│ └── Execute plan → quality gates
│
└── Phase 4: Review (reviewer agent)
└── Code review → commit
When asked to build a feature:
| Phase | Agent | Why |
|---|---|---|
| Research | scout (background, worktree) | Non-blocking exploration |
| Plan | orchestrator (opus, memory) | Deep reasoning, pattern recall |
| Implement | orchestrator (opus, memory) | Full tool access |
| Review | reviewer (read + bash) | Security and quality focus |
| Debug | debugger (opus, memory) | Systematic investigation |
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Coordinate multiple Claude Code sessions as a team — lead + teammates with shared task lists, mailbox messaging, and file-lock claiming. Patterns for team sizing, task decomposition, and when to use teams vs sub-agents vs worktrees.
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Auto-configure quality gates, hooks, and settings for a new project. Detects project type and sets up appropriate tooling. Use when onboarding a new codebase.
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Decompose large-scale changes into independent units and spawn parallel agents in isolated worktrees. Use for migrations, refactors, codemods, and any change touching 10+ files with the same pattern.
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Capture a user-reported defect as a durable GitHub issue written in the project's own domain language. Explores the codebase in parallel for context but never leaks file paths or line numbers into the issue. Use when the user reports a bug conversationally, runs a QA pass, or says "file an issue", "log this as a bug", "capture this".
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Smart context compaction with state preservation. Saves critical files, task progress, and working state before compaction, restores after. Use before manual compact or when auto-compact triggers.
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Master the four operations of context engineering — Write, Select, Compress, Isolate. Manage token budgets, compaction strategies, and context partitioning to keep AI sessions sharp and efficient.
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