Handoff logo

Handoff

Community
Tranz007
handoff

Prepare UX work for engineering by preserving user intent, behavior, states, design-system usage, accessibility requirements, dependencies, acceptance behavior, and unresolved questions. Use when a designer says "get this ready for engineering", needs a handoff, behavioral contract, implementation-ready ticket content, or wants to stop engineering from guessing.

Overview

PublisherTranz007
Repositoryux-skills
Skill namehandoff
Stars
48
Forks
4
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 Tranz007 on GitHub. Read the source before you install it.

Installation

Install the 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/Tranz007/ux-skills/tree/main/skills/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/Tranz007/ux-skills.git /tmp/ux-skills
mkdir -p .claude/skills
cp -r /tmp/ux-skills/skills/handoff .claude/skills/handoff
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable 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 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 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.

Handoff

Transfer design intent, not just appearance.

Always

  • Context — inspect what is already known before asking the user to repeat it. Use .ux/INTENT.md when product purpose or outcome can change the answer, and load only the additional project context the task needs.
  • User — ground the work in the people affected, their goal, task, context, and available evidence. Do not invent user needs, behaviors, or personas.
  • Evidence — keep known, inferred, assumed, unknown, and conflicted information distinct when the difference matters.
  • System — prefer established product language, components, patterns, and rules before inventing new ones.
  • Clear — lead with the useful point, use the minimum structure needed, and remove generic AI filler.
  • Trust — never invent evidence, requirements, rationale, implementation status, or compliance.
  • Outcome — for substantial multi-step work, keep intent active, use a small .ux/STATE.md only when continuity needs it, prioritize the highest-impact unresolved gap before polishing, and verify the actual experience against intent before declaring completion.

Do not recite these rules to the user unless one of them materially affects the answer.

Do not introduce research questions, personas, or discovery work when the user and task are already clear or the missing information would not materially change the work.

Gather the source of truth

Inspect the approved design, relevant flow and state decisions, design-system components, content, accessibility requirements, constraints, decision records, and the team's existing engineering workflow. Load only the project context needed to preserve the intended experience.

Do not describe proposed behavior as approved if its status is unclear.

Check readiness

Before packaging the work, look for anything that would force engineering to guess:

  • missing states or recovery;
  • ambiguous transitions;
  • unsupported new components or patterns;
  • unresolved content or terminology;
  • accessibility behavior that has not been defined;
  • data or service conditions that materially change the experience;
  • consequential decisions that are still open.

Do not block handoff for documentation that does not affect implementation.

Explain behavior

Prioritize what engineering actually needs:

  • user goal and outcome;
  • entry conditions and primary behavior;
  • meaningful branches and recovery;
  • component and pattern usage;
  • states and data conditions;
  • responsive behavior when relevant;
  • content rules and terminology;
  • accessibility behavior such as focus, announcements, semantics, and keyboard interaction when established;
  • dependencies and constraints;
  • unresolved questions.

When precision helps, describe behavior as:

text
When <condition>
→ the system <behavior>
→ the user <sees/hears/can do>
→ relevant state <persists/resets/changes>
→ recovery <behavior>

Fit the team's workflow

If the team needs Jira, GitHub Issues, Linear, Azure DevOps, or another ticket format, turn the handoff into buildable work without splitting it into meaningless UI fragments.

If the user only needs a handoff, do not create ticket-shaped output just because you can.

Output

Create the smallest engineering package that makes the intended experience clear and testable. Point to authoritative design-system, decision, research, intent, or design sources rather than duplicating them.

Contrast example

Bad:

Implement the updated verification screens according to Figma. Include loading and error states and make sure the experience is accessible.

Good:

When verification fails, remain on the current step, preserve the entered code, show the inline error, and move focus to the error summary. Reuse the existing Alert and verification-input patterns. The expired-code recovery path is still unresolved; engineering should not invent that behavior.

Why: the good handoff transfers behavior, system usage, accessibility intent, and unresolved decisions instead of handing engineering a picture plus vague instructions.

Examples

  • "Get this ready for engineering."
  • "Turn this approved flow into an implementation handoff."
  • "Write the behavior so engineering and QA can test it."
  • "Break this into buildable tickets without losing the UX intent."

Frequently asked questions

What does the Handoff AI skill do?

Prepare UX work for engineering by preserving user intent, behavior, states, design-system usage, accessibility requirements, dependencies, acceptance behavior, and unresolved questions. Use when a designer says "get this ready for engineering", needs a handoff, behavioral contract, implementation-ready ticket content, or wants to stop engineering from guessing.

Why use Handoff on TypingMind?

Because you install it once and use it with any model. 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 Handoff in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Tranz007/ux-skills/tree/main/skills/handoff. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use 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 Handoff?

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

Is the Handoff AI skill free?

Yes. It is published on GitHub by Tranz007 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.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇