research-lead-sidecar

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Use when the user wants multi-agent division of labor for research-led work and the lead should stay on the critical path while 1-2 bounded sidecars handle low-coupling tasks. Do not use this for tiny tasks, fully sequential debugging, or overlapping refactors.

cnfjlhj By cnfjlhj schedule Updated 4/4/2026

name: research-lead-sidecar description: Use when the user wants multi-agent division of labor for research-led work and the lead should stay on the critical path while 1-2 bounded sidecars handle low-coupling tasks. Do not use this for tiny tasks, fully sequential debugging, or overlapping refactors.

Research Lead Sidecar

Overview

Use this skill for research-led work where implementation and evidence gathering are coupled, but the main agent should remain the lead. It keeps the critical path local while bounded sidecars handle non-blocking scout, worker, verifier, or writer tasks.

Rules

  • Keep the lead responsible for framing, synthesis, and final decisions.
  • Delegate only tasks that are non-blocking, bounded, inspectable, and recoverable.
  • Prefer 1-2 sidecars with clear roles instead of spawning a crowd by default.
  • The lead should keep moving on the critical path instead of waiting idly for sidecars.
  • Use milestone verification and durable workspace state only when the task span justifies them.

When to Use

Use when:

  • the user explicitly wants 多智能体分工, research-led multi-agent work, or long-task governance with a lead agent
  • there is one critical path plus a small number of low-coupling side tasks
  • sidecars can return artifacts the lead can inspect quickly

Do not use when:

  • the task is tiny, fully sequential, or blocked on each previous result
  • several agents would need to touch the same hot files or same narrow context
  • handoff cost is higher than simply doing the work locally
Install via CLI
npx skills add https://github.com/cnfjlhj/ai-collab-playbook --skill research-lead-sidecar
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