orchestrate
Wire Commands, Agents, and Skills together for complex features. Use when building features that need research, planning, and implementation phases.
Best use case
orchestrate is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Wire Commands, Agents, and Skills together for complex features. Use when building features that need research, planning, and implementation phases.
Teams using orchestrate should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/orchestrate/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How orchestrate Compares
| Feature / Agent | orchestrate | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Wire Commands, Agents, and Skills together for complex features. Use when building features that need research, planning, and implementation phases.
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
# Orchestrate - Multi-Phase Feature Development
Build features through structured phases with validation gates.
## The Pattern
```text
/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
```
## Usage
When asked to build a feature:
1. **Start with research**: Delegate to the orchestrator agent or scout agent to explore the codebase
2. **Wait for GO/HOLD**: Don't proceed if confidence is below 70
3. **Present a plan**: List all files to change, the approach, and risks
4. **Get approval**: Never implement without explicit "proceed"
5. **Implement step by step**: Quality gates every 5 edits
6. **Review before commit**: Run the reviewer agent on changes
## When to Use This
- Feature touches >5 files
- Architecture decisions needed
- Requirements are unclear or complex
- Cross-cutting concerns (auth, logging, error handling)
- New patterns not yet established in the codebase
## When NOT to Use This
- Quick bug fixes (just fix it)
- Single-file changes
- Well-understood patterns (follow existing code)
- Documentation-only changes
## Agent Selection
| 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 |
## Integration with Pro-Workflow
- Corrections during implementation trigger self-correction loop
- Quality gates fire at checkpoints via hooks
- Learnings are captured at the end of each phase
- Session handoff works across phasesRelated Skills
wrap-up
End-of-session ritual that audits changes, runs quality checks, captures learnings, and produces a session summary. Use when saying "wrap up", "done for the day", "finish coding", or ending a coding session.
thoroughness-scoring
Score every decision point with a Thoroughness Rating (1-10). AI makes the marginal cost of doing things properly near-zero — pick the higher-rated option every time. Includes scope checks to distinguish contained vs unbounded work.
sprint-status
Track parallel work sessions and prevent confusion across multiple Claude Code instances. Every major step ends with a status line. Every question re-states project, branch, and task.
smart-commit
Run quality gates, review staged changes for issues, and create a well-crafted conventional commit. Use when saying "commit", "git commit", "save my changes", or ready to commit after making changes.
session-handoff
Generate a structured handoff document capturing current progress, open tasks, key decisions, and context needed to resume work. Use when ending a session, saying "continue later", "save progress", "session summary", or "pick up where I left off".
safe-mode
Prevent destructive operations using Claude Code hooks. Three modes — cautious (warn on dangerous commands), lockdown (restrict edits to one directory), and clear (remove restrictions). Uses PreToolUse matchers for Bash, Edit, and Write.
replay-learnings
Surface past learnings relevant to the current task before starting work. Searches correction history, recalls past mistakes, and applies prior patterns. Use when starting a task, saying "what do I know about", "previous mistakes", "lessons learned", or "remind me about".
pro-workflow
Complete AI coding workflow system. Orchestration patterns, 18 hook events, 5 agents, cross-agent support, reference guides, and searchable learnings. Works with Claude Code, Cursor, and 32+ agents.
permission-tuner
Analyze permission denial patterns and generate optimized alwaysAllow and alwaysDeny rules. Use when permission prompts are slowing you down or after sessions with many denials.
parallel-worktrees
Create and manage git worktrees for parallel coding sessions with zero dead time. Use when blocked on tests, builds, wanting to work on multiple branches, context switching, or exploring multiple approaches simultaneously.
mcp-audit
Audit connected MCP servers for token overhead, redundancy, and security. Use when sessions feel slow or before adding new MCPs.
llm-gate
LLM-powered quality verification using prompt hooks. Validates commit messages, code patterns, and conventions using AI before allowing operations. Use to set up intelligent guardrails.