paseo-handoff▌
getpaseo/paseo · updated Apr 8, 2026
MDX-style export adds YAML metadata + attribution linking explainx.ai and this canonical listing URL.
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.
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:
- Provider and model — who to hand off to
- Worktree — whether to run in an isolated git worktree
- 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
- Task description — What needs to be done, in clear imperative language
- 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
- Relevant files — List every file path that matters, with brief descriptions of what each contains
- Current state — What has been done so far, what's working, what's not
- What was tried — Any approaches attempted and why they failed or were abandoned
- Decisions made — Anything you and the user agreed on (design choices, constraints, trade-offs)
- Acceptance criteria — How the agent knows it's done
- 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
- 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> - Do not wait for the agent by default — the user can choose to wait or move on.
- If the user wants to wait, run
paseo wait <id>and thenpaseo logs <id>when done.
How to use paseo-handoff 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-handoff
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches paseo-handoff 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-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
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
4.4★★★★★73 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