paseo-committee

getpaseo/paseo · updated Apr 8, 2026

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$npx skills add https://github.com/getpaseo/paseo --skill paseo-committee
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summary

You are forming a committee to step back from the current problem and get fresh perspective.

skill.md

Committee Skill

You are forming a committee to step back from the current problem and get fresh perspective.

User's additional context: $ARGUMENTS


Prerequisites

Load the Paseo skill first — it contains the CLI reference for all agent commands and waiting guidelines.

What Is a Committee

Two agents — Opus 4.6 (--thinking on) and GPT 5.4 (--thinking medium) — launched in parallel to plan a solution. Fresh context, no implementation baggage, proper root cause analysis.

They stay alive after planning for Phase 3 review — they hold only the plan, so they catch implementation drift.

The purpose is to step back, not to double down. The committee may propose a completely different approach.

Your Role

You drive the full lifecycle: plan → implement → review. You are a middleman between the user and the committee. Do not yield back to the user until the cycle is complete. If the user needs to weigh in on a divergence, ask them — but don't stop the process.

No Anxiety

Once you call paseo wait, trust the wait. Do not poll logs, read output early, send hurry-up messages, interrupt deep analysis, or give up because it's taking long.

GPT 5.4 can reason for 15–30 minutes. Opus does extended thinking. Long waits mean the agent found something worth thinking about. Let it finish.

If the CLI has a bug, the user will tell you.

No-Edits Suffix

Every prompt to a committee member — initial, follow-up, or review — must end with this suffix. They will start editing code if you don't.

NO_EDITS="This is analysis only. Do NOT edit, create, or delete any files. Do NOT write code."

All example prompts below include $NO_EDITS — always expand it.

Phase 1: Get a Plan

Write the prompt

Describe the overall problem, not just the immediate symptom:

  • High-level goal and acceptance criteria
  • Constraints
  • Symptoms (if a bug)
  • What you've tried and why it failed
  • Explicitly ask for root cause analysis
prompt="We're trying to [high-level goal]. Constraints: [X, Y, Z]. Acceptance criteria: [A, B, C].

We've been stuck on this. Here's what we've tried and why it didn't work:
- [approach 1] — failed because [reason]
- [approach 2] — partially worked but [issue]

Step back from these attempts. Do root cause analysis — the fix might not be for [immediate symptom] at all, it might be structural.

Use the think-harder approach: state your assumptions, ask why at least 3 levels deep for each, and check whether you're patching a symptom or removing the problem. What's the right approach?

$NO_EDITS"

Launch both members

Same prompt to both, [Committee] prefix for identification:

opus_id=$(paseo run -d --mode bypassPermissions --provider claude/opus --thinking on --name "[Committee] Task description" "$prompt" -q)
gpt_id=$(paseo run -d --mode full-access --provider codex/gpt-5.4 --thinking medium --name "[Committee] Task description" "$prompt" -q)

Wait for both

Wait for both agents — not just the first one that finishes.

paseo wait "$opus_id"
paseo wait "$gpt_id"

Read and challenge

paseo logs "$opus_id"
paseo logs "$gpt_id"

Do not accept output at face value. Use the think-harder framework to challenge their output. Before synthesizing:

  1. Ask "why" 2–3 levels deep. "Fix X because Y is broken" — why is Y broken? Is Y a root cause or a consequence?
  2. Challenge assumptions. If the plan assumes something about the code, make the agent verify it.
  3. Symptom vs cause. "Are we fixing the consequence or the cause?"
  4. Probe alternatives. "What did you consider and reject?"
paseo send "$opus_id" "You said [X]. Why does [underlying thing] happen in the first place? Are we patching a symptom? $NO_EDITS"
paseo wait "$opus_id"
paseo logs "$opus_id"

Keep pushing until the plan addresses the root cause.

Synthesize and confirm

  • Convergence → merge into unified plan.
  • Significant divergence → involve the user.

Send the merged plan back for confirmation. Multi-turn if needed — keep going until consensus.

paseo send "$opus_id" "Merged plan: [plan]. Concerns? $NO_EDITS"
paseo send "$gpt_id" "Merged plan: [plan]. Concerns? $NO_EDITS"

Phase 2: Implement

Implement the plan yourself — unless the user said "delegate", in which case launch an implementer:

impl_id=$(paseo run -d --mode full-access --provider codex/gpt-5.4 --name "[Impl] Task description" "Implement the following plan end-to-end. [plan]" -q)
paseo wait "$impl_id"

Committee agents stay clean — not involved in implementation.

Phase 3: Review

Send the committee the changes for review. They anchor against the plan and catch drift.

review_prompt="Implementation is done. Review changes against the plan. Flag drift or missing pieces. $NO_EDITS"

paseo send "$opus_id" "$review_prompt"
paseo send "$gpt_id" "$review_prompt"

paseo wait "$opus_id"
paseo wait "$gpt_id"

paseo logs "$opus_id"
paseo logs "$gpt_id"

Iterate

Send committee feedback to the implementer (or apply yourself). Repeat Phase 2 → 3 until the committee confirms the implementation matches the plan.

After ~10 iterations without convergence, start a fresh committee with full context of what was tried — the current committee's context may have drifted too far.

how to use paseo-committee

How to use paseo-committee on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your development machine
  • Node.js version 16.0+ with npm package manager (verify with node --version)
  • Active project directory or workspace where you want to add paseo-committee
2

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/getpaseo/paseo --skill paseo-committee

The skills CLI fetches paseo-committee from GitHub repository getpaseo/paseo and configures it for Cursor.

3

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ── always included ────
│ • Amp
│ • Antigravity
│ • Cline
│ • Codex
│ ●Cursor(selected)
│ • Cursor
│ • Windsurf
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/paseo-committee

Reload or restart Cursor to activate paseo-committee. Access the skill through slash commands (e.g., /paseo-committee) or your agent's skill management interface.

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

Improve work quality by 30-40% with less effort

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client with skill support
  • Clear understanding of task or problem to solve
  • Willingness to iterate and refine outputs

Time Estimate

15-45 minutes depending on use case complexity

Installation Steps

  1. 1.Install skill using provided installation command
  2. 2.Test with simple use case relevant to your work
  3. 3.Evaluate output quality and relevance
  4. 4.Iterate on prompts to improve results
  5. 5.Integrate into regular workflow if valuable

Common Pitfalls

  • Expecting perfect results without iteration
  • Not providing enough context in prompts
  • Using skill for tasks outside its intended scope
  • Accepting outputs without review and validation

Best Practices

✓ Do

  • +Start with clear, specific prompts
  • +Provide relevant context and constraints
  • +Review and refine all outputs before using
  • +Iterate to improve output quality
  • +Document successful prompt patterns

✗ Don't

  • Don't use without understanding skill limitations
  • Don't skip validation of outputs
  • Don't share sensitive information in prompts
  • Don't expect skill to replace human judgment

💡 Pro Tips

  • Be specific about desired format and style
  • Ask for multiple options to choose from
  • Request explanations to understand reasoning
  • Combine AI efficiency with human expertise

When to Use This

✓ Use When

Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.

✗ Avoid When

Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.

Learning Path

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Discussion

Product Hunt–style comments (not star reviews)
  • No comments yet — start the thread.
general reviews

Ratings

4.856 reviews
  • Xiao Gonzalez· Dec 28, 2024

    paseo-committee reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Camila Sethi· Dec 24, 2024

    We added paseo-committee from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Noor Chen· Dec 16, 2024

    Registry listing for paseo-committee matched our evaluation — installs cleanly and behaves as described in the markdown.

  • Diego Nasser· Nov 19, 2024

    We added paseo-committee from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Daniel Khan· Nov 15, 2024

    paseo-committee reduced setup friction for our internal harness; good balance of opinion and flexibility.

  • Noor Brown· Nov 7, 2024

    paseo-committee fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • Meera Menon· Nov 7, 2024

    Solid pick for teams standardizing on skills: paseo-committee is focused, and the summary matches what you get after install.

  • Noor Sanchez· Oct 26, 2024

    We added paseo-committee from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.

  • Noor Yang· Oct 26, 2024

    paseo-committee has been reliable in day-to-day use. Documentation quality is above average for community skills.

  • Anika Okafor· Oct 10, 2024

    paseo-committee fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

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