agent-orchestration
Instructs AI to use sub-agents for complex multi-file tasks instead of performing them in the main chat context.
Install
mkdir -p .claude/skills/agent-orchestration && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/2193" && unzip -o skill.zip -d .claude/skills/agent-orchestration && rm skill.zipInstalls to .claude/skills/agent-orchestration
Activation
This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.
Agent Orchestration RulesKey capabilities
- →Spawn implementation agents for multi-file tasks
- →Offload plan execution to sub-agents
- →Preserve main conversation context
- →Summarize agent task results
- →Execute multi-file codebase refactoring
How it works
The skill orchestrates sub-agents to handle complex, multi-file implementation tasks, keeping the main conversation context focused and token-efficient.
Inputs & outputs
When to use agent-orchestration
- →Implementing complex features from a plan
- →Multi-file codebase refactoring
- →Running tests after a code change
About this skill
Agent Orchestration Rules
When the user asks to implement something, use implementation agents to preserve main context.
The Pattern
Wrong - burns context:
Main: Read files → Understand → Make edits → Report
(2000+ tokens consumed in main context)
Right - preserves context:
Main: Spawn agent("implement X per plan")
↓
Agent: Reads files → Understands → Edits → Tests
↓
Main: Gets summary (~200 tokens)
When to Use Agents
| Task Type | Use Agent? | Reason |
|---|---|---|
| Multi-file implementation | Yes | Agent handles complexity internally |
| Following a plan phase | Yes | Agent reads plan, implements |
| New feature with tests | Yes | Agent can run tests |
| Single-line fix | No | Faster to do directly |
| Quick config change | No | Overhead not worth it |
Key Insight
Agents read their own context. Don't read files in main chat just to understand what to pass to an agent - give them the task and they figure it out.
Example Prompt
Implement Phase 4: Outcome Marking Hook from the Artifact Index plan.
**Plan location:** thoughts/shared/plans/2025-12-24-artifact-index.md (search for "Phase 4")
**What to create:**
1. TypeScript hook
2. Shell wrapper
3. Python script
4. Register in settings.json
When done, provide a summary of files created and any issues.
Trigger Words
When user says these, consider using an agent:
- "implement", "build", "create feature"
- "follow the plan", "do phase X"
- "use implementation agents"
When not to use it
- →For single-line code fixes
- →For quick configuration changes
Limitations
- →Overhead is not justified for simple tasks
- →Requires clear task definition for sub-agents
How it compares
It offloads complexity to specialized agents rather than performing all operations within the main chat context.
Compared to similar skills
agent-orchestration side by side with the closest alternatives in the catalog.
| Skill | Installs | Updated | Safety | Difficulty |
|---|---|---|---|---|
| agent-orchestration (this skill) | 3 | 7mo | No flags | Intermediate |
| agent-factory | 8 | 9mo | Review | Advanced |
| claude-opus-4-5-migration | 9 | 8mo | No flags | Beginner |
| subagent-driven-development | 14 | 7mo | No flags | Advanced |
Try saying
Example prompts that trigger this skill in your AI assistant.
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