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Create Handoff

Community
vibeeval
create-handoff

Create handoff document for transferring work to another session

Overview

Publishervibeeval
Repositoryvibecosystem
Skill namecreate-handoff
Stars
541
Forks
44
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by vibeeval on GitHub. Read the source before you install it.

Installation

Install the Create Handoff AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/vibeeval/vibecosystem/tree/main/skills/create-handoff
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/vibeeval/vibecosystem.git /tmp/vibecosystem
mkdir -p .claude/skills
cp -r /tmp/vibecosystem/skills/create-handoff .claude/skills/create-handoff
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Create Handoff in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Create Handoff on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Create Handoff is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Create Handoff

You are tasked with writing a handoff document to hand off your work to another agent in a new session. You will create a handoff document that is thorough, but also concise. The goal is to compact and summarize your context without losing any of the key details of what you're working on.

Process

1. Filepath & Metadata

Use the following information to understand how to create your document:

First, determine the session name from existing handoffs:

bash
ls -td thoughts/shared/handoffs/*/ 2>/dev/null | head -1 | xargs basename

This returns the most recently modified handoff folder name (e.g., open-source-release). Use this as the handoff folder name.

If no handoffs exist, use general as the folder name.

Create your file under: thoughts/shared/handoffs/{session-name}/YYYY-MM-DD_HH-MM_description.yaml, where:

  • {session-name} is from existing handoffs (e.g., open-source-release) or general if none exist
  • YYYY-MM-DD is today's date
  • HH-MM is the current time in 24-hour format (no seconds needed)
  • description is a brief kebab-case description

Examples:

  • thoughts/shared/handoffs/open-source-release/2026-01-08_16-30_memory-system-fix.yaml
  • thoughts/shared/handoffs/general/2026-01-08_16-30_bug-investigation.yaml

2. Write YAML handoff (~400 tokens vs ~2000 for markdown)

CRITICAL: Use EXACTLY this YAML format. Do NOT deviate or use alternative field names.

The goal: and now: fields are shown in the statusline - they MUST be named exactly this.

yaml
---
session: {session-name from ledger}
date: YYYY-MM-DD
status: complete|partial|blocked
outcome: SUCCEEDED|PARTIAL_PLUS|PARTIAL_MINUS|FAILED
---

goal: {What this session accomplished - shown in statusline}
now: {What next session should do first - shown in statusline}
test: {Command to verify this work, e.g., pytest tests/test_foo.py}

done_this_session:
  - task: {First completed task}
    files: [{file1.py}, {file2.py}]
  - task: {Second completed task}
    files: [{file3.py}]

blockers: [{any blocking issues}]

questions: [{unresolved questions for next session}]

decisions:
  - {decision_name}: {rationale}

findings:
  - {key_finding}: {details}

worked: [{approaches that worked}]
failed: [{approaches that failed and why}]

next:
  - {First next step}
  - {Second next step}

files:
  created: [{new files}]
  modified: [{changed files}]

Field guide:

  • goal: + now: - REQUIRED, shown in statusline
  • done_this_session: - What was accomplished with file references
  • decisions: - Important choices and rationale
  • findings: - Key learnings
  • worked: / failed: - What to repeat vs avoid
  • next: - Action items for next session

DO NOT use alternative field names like session_goal, objective, focus, current, etc. The statusline parser looks for EXACTLY goal: and now: - nothing else works.

3. Mark Session Outcome (REQUIRED)

IMPORTANT: Before responding to the user, you MUST ask about the session outcome.

Use the AskUserQuestion tool with these exact options:

Question: "How did this session go?"
Options:
  - SUCCEEDED: Task completed successfully
  - PARTIAL_PLUS: Mostly done, minor issues remain
  - PARTIAL_MINUS: Some progress, major issues remain
  - FAILED: Task abandoned or blocked

After the user responds, mark the outcome:

bash
# Mark the most recent handoff (works with PostgreSQL or SQLite)
# Use git root to find project, then opc/scripts/core/
PROJECT_ROOT=$(git rev-parse --show-toplevel 2>/dev/null || echo "${CLAUDE_PROJECT_DIR:-.}")
cd "$PROJECT_ROOT/opc" && uv run python scripts/core/artifact_mark.py --latest --outcome <USER_CHOICE>

This command auto-detects the database (PostgreSQL if configured, SQLite fallback).

4. Confirm completion

After marking the outcome, respond to the user:

Handoff created! Outcome marked as [OUTCOME].

Resume in a new session with:
/resume_handoff path/to/handoff.yaml

##. Additional Notes & Instructions

  • more information, not less. This is a guideline that defines the minimum of what a handoff should be. Always feel free to include more information if necessary.
  • be thorough and precise. include both top-level objectives, and lower-level details as necessary.
  • avoid excessive code snippets. While a brief snippet to describe some key change is important, avoid large code blocks or diffs; do not include one unless it's necessary (e.g. pertains to an error you're debugging). Prefer using /path/to/file.ext:line references that an agent can follow later when it's ready, e.g. packages/dashboard/src/app/dashboard/page.tsx:12-24

Frequently asked questions

What does the Create Handoff AI skill do?

Create handoff document for transferring work to another session

Why use Create Handoff on TypingMind?

Because you install it once and use it with any model. Create Handoff is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Create Handoff in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/vibeeval/vibecosystem/tree/main/skills/create-handoff. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Create Handoff?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Create Handoff?

As many as you like. As long as a model supports skills, you can use Create Handoff with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Create Handoff AI skill free?

Yes. It is published on GitHub by vibeeval under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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