paseo-handoff

getpaseo/paseo · updated Apr 8, 2026

MDX-style export adds YAML metadata + attribution linking explainx.ai and this canonical listing URL.

$npx skills add https://github.com/getpaseo/paseo --skill paseo-handoff
0 commentsdiscussion
summary

You are handing off the current task to another agent. Your job is to write a comprehensive handoff prompt and launch the agent via Paseo CLI.

skill.md

Handoff Skill

You are handing off the current task to another agent. Your job is to write a comprehensive handoff prompt and launch the agent via Paseo CLI.

User's arguments: $ARGUMENTS


Prerequisites

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

What Is a Handoff

A handoff transfers your current task — including all context, decisions, failed attempts, and constraints — to a fresh agent that will carry it to completion. The handoff prompt is the most important part: the receiving agent starts with zero context, so everything it needs must be in the prompt.

Parsing Arguments

Parse $ARGUMENTS to determine:

  1. Provider and model — who to hand off to
  2. Worktree — whether to run in an isolated git worktree
  3. Task description — any additional context the user provided

Provider Resolution

User says --provider Mode
(nothing) codex/gpt-5.4 full-access
codex codex/gpt-5.4 full-access
claude claude/opus bypass
opus claude/opus bypass
sonnet claude/sonnet bypass

Default is Codex with gpt-5.4.

Worktree Resolution

If the user says "in a worktree" or "worktree", add --worktree with a short descriptive branch name derived from the task. Worktrees require a --base branch — use the current branch in the working directory (run git branch --show-current to get it).

Writing the Handoff Prompt

This is the critical step. The receiving agent has zero context about your conversation. The handoff prompt must be a self-contained briefing document.

Must Include

  1. Task description — What needs to be done, in clear imperative language
  2. Task qualifiers — Preserve the semantics of what the user asked for:
    • If the user asked to investigate without editing, say "DO NOT edit any files"
    • If the user asked to fix, say "implement the fix"
    • If the user asked to refactor, say "refactor" not "rewrite"
    • Carry forward the exact intent
  3. Relevant files — List every file path that matters, with brief descriptions of what each contains
  4. Current state — What has been done so far, what's working, what's not
  5. What was tried — Any approaches attempted and why they failed or were abandoned
  6. Decisions made — Anything you and the user agreed on (design choices, constraints, trade-offs)
  7. Acceptance criteria — How the agent knows it's done
  8. Constraints — Anything the agent must NOT do

Template

## Task

[Clear, imperative description of what to do]

## Context

[Why this task exists, background the agent needs]

## Relevant Files

- `path/to/file.ts` — [what it does and why it matters]
- `path/to/other.ts` — [what it does and why it matters]

## Current State

[What's been done, what works, what doesn't]

## What Was Tried

- [Approach 1] — [why it failed/was abandoned]
- [Approach 2] — [partial success, but...]

## Decisions

- [Decision 1 — rationale]
- [Decision 2 — rationale]

## Acceptance Criteria

- [ ] [Criterion 1]
- [ ] [Criterion 2]

## Constraints

- [Do not do X]
- [Must preserve Y]

Launching the Agent

Default (Codex, no worktree)

paseo run -d --mode full-access --provider codex/gpt-5.4 --name "[Handoff] Task description" "$prompt"

Claude (Opus, no worktree)

paseo run -d --mode bypassPermissions --provider claude/opus --name "[Handoff] Task description" "$prompt"

Codex in a worktree

base=$(git branch --show-current)
paseo run -d --mode full-access --provider codex/gpt-5.4 --worktree task-branch-name --base "$base" --name "[Handoff] Task description" "$prompt"

Claude in a worktree

base=$(git branch --show-current)
paseo run -d --mode bypass --provider claude/opus --worktree task-branch-name --base "$base" --name "[Handoff] Task description" "$prompt"

After Launch

  1. Print the agent ID and the command to follow along:
    Handed off to [provider] ([model]). Agent ID: <id>
    Follow along: paseo logs <id> -f
    Wait for completion: paseo wait <id>
    
  2. Do not wait for the agent by default — the user can choose to wait or move on.
  3. If the user wants to wait, run paseo wait <id> and then paseo logs <id> when done.
how to use paseo-handoff

How to use paseo-handoff 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-handoff
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-handoff

The skills CLI fetches paseo-handoff 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-handoff

Reload or restart Cursor to activate paseo-handoff. Access the skill through slash commands (e.g., /paseo-handoff) 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

4.473 reviews
  • Hana Khan· Dec 24, 2024

    paseo-handoff is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • Aisha Iyer· Dec 24, 2024

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

  • Pratham Ware· Dec 20, 2024

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

  • Aisha Gupta· Dec 20, 2024

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

  • Alexander Mensah· Dec 20, 2024

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

  • William Nasser· Dec 16, 2024

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

  • Min Dixit· Dec 8, 2024

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

  • Kabir Garcia· Dec 4, 2024

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

  • Ava Bansal· Nov 15, 2024

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

  • Aanya Park· Nov 15, 2024

    Useful defaults in paseo-handoff — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

showing 1-10 of 73

1 / 8