paseo-loop▌
getpaseo/paseo · updated Apr 8, 2026
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You are setting up a loop — an iterative worker/verifier cycle managed by the Paseo daemon.
Paseo Loop Skill
You are setting up a loop — an iterative worker/verifier cycle managed by the Paseo daemon.
User's arguments: $ARGUMENTS
Prerequisites
Load the Paseo skill first. It contains the CLI reference for paseo loop and related commands.
Core Model
A loop repeats: launch a worker → verify → repeat until done or limits hit.
- Worker prompt: what the worker does each iteration
- Verification: verifier prompt and/or shell checks that judge success
- Sleep: optional pause between iterations
- Stop conditions: max iterations and/or max total runtime
- Model selection: different providers/models for worker vs verifier
- Archive: optionally preserve agent history after each iteration
Verification
Every loop needs at least one form of verification:
--verify "<prompt>"— a verifier agent judges the worker's output--verify-check "<command>"— a shell command that must exit 0 (repeatable)- Both can be combined: shell checks run first, then the verifier prompt
Model Selection
Choose the right provider/model for worker and verifier independently:
--provider <provider/model>— sets the worker (e.g.codex/gpt-5.4)--verify-provider <provider/model>— sets the verifier (e.g.claude/opus)
Default: both use Claude/sonnet. For implementation loops, use Codex for the worker and Claude for the verifier — each catches the other's blind spots.
Archive
--archive preserves worker and verifier agents after each iteration instead of destroying them. Use this when you need to inspect conversation history for debugging.
Defaults by User Intent
Babysit / watch / check every X
paseo loop run "Check PR #42. Review CI, comments, and branch status. Fix issues as they arise." \
--verify-check "gh pr checks 42 --fail-fast" \
--sleep 2m \
--max-time 1h \
--name babysit-pr-42
Keep trying until tests pass
paseo loop run "Run the test suite, investigate failures, and fix the code." \
--provider codex/gpt-5.4 \
--verify "Run the test suite. Return done=true only if all tests pass. Cite the exact command and outcome." \
--verify-check "npm test" \
--max-iterations 10 \
--name fix-tests
Implementation loop with cross-provider review
paseo loop run "Implement issue #456. Make incremental progress each iteration." \
--provider codex/gpt-5.4 \
--verify "Verify issue #456 is complete. Check changed files, run typecheck and tests." \
--verify-provider claude/sonnet \
--max-iterations 8 \
--max-time 2h \
--archive \
--name issue-456
Managing Loops
paseo loop ls # List all loops
paseo loop inspect <id> # Show details and iteration history
paseo loop logs <id> # Stream logs
paseo loop stop <id> # Stop a running loop
Your Job
- Understand the user's intent from the conversation and
$ARGUMENTS - Decide the worker prompt — self-contained, concrete about what to do
- Decide verification — shell checks for objective criteria, verifier prompt for judgment
- Choose providers/models for worker and verifier
- Choose sleep only when the task is polling or waiting on an external system
- Add sensible stop conditions
- Run
paseo loop runwith the final arguments
Prompt Writing Rules
Worker prompt
The worker prompt must be:
- self-contained
- concrete about commands, files, branches, tests, PRs, or systems to inspect
- explicit about what counts as progress this iteration
Verifier prompt
The verifier prompt should:
- check facts, not offer fixes
- cite commands, outputs, or file evidence
- be specific about what "done" means
How to use paseo-loop on Cursor
AI-first code editor with Composer
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-loop
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches paseo-loop from GitHub repository getpaseo/paseo and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate paseo-loop. Access the skill through slash commands (e.g., /paseo-loop) 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
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.Install skill using provided installation command
- 2.Test with simple use case relevant to your work
- 3.Evaluate output quality and relevance
- 4.Iterate on prompts to improve results
- 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▌
- 1Familiarize yourself with skill capabilities and limitations
- 2Start with low-risk, non-critical tasks
- 3Progress to more complex and valuable use cases
- 4Build expertise through regular use and experimentation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.6★★★★★70 reviews- ★★★★★Ganesh Mohane· Dec 28, 2024
We added paseo-loop from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Chinedu Malhotra· Dec 28, 2024
Solid pick for teams standardizing on skills: paseo-loop is focused, and the summary matches what you get after install.
- ★★★★★Shikha Mishra· Dec 24, 2024
I recommend paseo-loop for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Chinedu Khanna· Dec 24, 2024
paseo-loop has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Luis Singh· Dec 24, 2024
paseo-loop fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Ama Ramirez· Dec 20, 2024
Keeps context tight: paseo-loop is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Camila Okafor· Dec 20, 2024
paseo-loop reduced setup friction for our internal harness; good balance of opinion and flexibility.
- ★★★★★Luis Verma· Dec 16, 2024
I recommend paseo-loop for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Emma Farah· Dec 12, 2024
Registry listing for paseo-loop matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Chinedu Verma· Nov 27, 2024
paseo-loop reduced setup friction for our internal harness; good balance of opinion and flexibility.
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