Multi agent supervisor
Skill m00kk/agent-skills-playbook/skills/multi-agent-supervisor
Implements the supervisor pattern: one orchestrator routes tasks to specialist agents (research, code, data). Use for multi-agent systems, delegating subtasks, LangGraph supervisor, or MCP-backed specialist workers.From its SKILL.md
npx -y skills add m00kk/agent-skills-playbook --skill multi-agent-supervisorAssembled from the repository path, not quoted from the project. Check it against their README if it does not work.
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SKILL.md
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Multi-Agent Supervisor
Architecture
User → Supervisor (routing only) → Specialist A | B | C → Supervisor → FINISH
Rule: Supervisor never executes tools directly — only picks the next worker.
Specialist design
| Specialist | Tools (via MCP) | Output |
|---|---|---|
| research | web_search, fetch_page | citations + summary |
| code | run_tests, lint, edit_files | patch or PR-ready diff |
| data | sql_query (read-only) | tables + interpretation |
Each specialist is a small ReAct or tool-calling subgraph with 2–5 tools max.
Routing prompt (supervisor)
Include in system message:
- List of workers with one-line capability
- Output format: exactly one of
[research, code, data, FINISH] - Stop when user goal satisfied; do not loop specialists unnecessarily
LangGraph sketch
- Node
supervisor— LLM returns next worker name - Nodes
research,code,data— run specialist; return to supervisor - Conditional edge from supervisor to worker or END
Failure handling
- Unknown route → default to clarifying question node
- Specialist error → append error to state; supervisor may retry once or escalate
- Max iterations (e.g. 15) to prevent infinite delegation
Scale-out
Add specialists by:
- New MCP server with focused tools
- New graph node + supervisor prompt line
- No change to other specialists
Pair with a2a-agent-delegation for cross-runtime agents.
What ships with it
Read from the repository
Just SKILL.md. No reference files, no scripts.