Paseo Committee
AI agents & workflows5.2K installs
What it does
Form a committee of two high-reasoning agents to step back, do root cause analysis, and produce a plan. Use when stuck, looping, tunnel-visioning, or facing a hard planning problem.
Install
npx skills add https://github.com/getpaseo/paseo --skill paseo-committeeWebsite
www.skills.sh/getpaseo/paseo/paseo-committeeDetails
From the skill’s SKILL.md or README, by its authors. View the original
Committee Skill
Two agents from contrasting profiles, fresh context, planning a solution in parallel.
Use the user's request and current conversation as input, including any arguments supplied with the skill invocation.
Prerequisites
Read the paseo skill. Call list_profiles before choosing committee members. Do not create committee agents until you have read the configured profiles and their notes.
Contrast is the point of a committee, so pick profiles from different provider families when possible. Materialize each profile into create_agent.
Composition
Two members with different reasoning styles, selected from configured Agent profiles:
- one whose notes fit planning, research, or root-cause analysis
- one contrasting high-reasoning profile from another provider family
If the user names profiles, use those. If fewer than two suitable profiles are configured, use Paseo's provider discovery fallback for the missing member and tell the user. Override the selection only when the user explicitly asks for different members.
Hard rules
- No edits. Every prompt to a committee member ends with the no-edits suffix:
This is analysis only. Do NOT edit, create, or delete any files. Do NOT write code.
- Trust the finish notification. Do not poll, send hurry-ups, or interrupt. Models can reason for 15–30 minutes. You can go idle and Paseo will notify you.
Workflow
- Write a problem-level prompt
- Create both agents in parallel via Paseo with
[Committee]titles and the same prompt - Wait for both responses
- Resolve disagreements by passing their arguments between each other
- Keep going until they converge into a response
Share the consensus with the user. Summarize where the agents diverged and how they resolved it.
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