Handoff logo

Handoff

CommunityPopular
jeremylongshore
handoff

Use when managing a two-session handoff — inspecting, picking up, or reviewing a committed handoff package produced by a session=two scope run. The operator interface over the cross-environment handoff lifecycle (plan in one session, build in another, review back in the first). Trigger with /hyperflow:handoff, "list handoffs", "pick up the handoff", "review the handoff build".

Overview

Publisherjeremylongshore
Repositorytons-of-skills-marketplace
Skill namehandoff
Stars
2.8K
Forks
402
Bundled files
Instructions only
LicenseMIT
Links
Skill sourceRepositoryHomepage
  • 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 jeremylongshore 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.
  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/jeremylongshore/tons-of-skills-marketplace.git /tmp/tons-of-skills-marketplace
mkdir -p .claude/skills
cp -r /tmp/tons-of-skills-marketplace/plugins/ai-agency/hyperflow/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

Operator interface for two-session execution: one session plans (session=two at the Step 0 gate), a second session in another environment builds, and the first session reviews. The lifecycle and package format are defined in ../hyperflow/session-handoff.md; this skill is the thin set of verbs over it (mirrors how /hyperflow:flush fronts the deferred-commit machinery).

Packages live at .hyperflow-handoff/<slug>/ (committed, so they travel via git). STATUS (planned → built → reviewed) is the single source of truth and decides which side of the handoff you are on.

Subcommands

list

Read-only. List every .hyperflow-handoff/*/ (excluding .archive/): slug · STATUS · on_complete · age. Group by status so the user sees what is awaiting build vs awaiting review.

status [<slug>]

Show the HANDOFF.md manifest + STATUS for one package (or all). When STATUS=built, also print the COMPLETION.md diff range and commit count. Read-only.

pickup <slug> — build side

Thin alias for starting the second-session build: invoke Skill with skill: dispatch and args: "<slug>". Dispatch's Step 1.0 rehydrates artefact/ into .hyperflow/, runs /hyperflow:scaffold if the cache is missing, builds the batches, writes COMPLETION.md + STATUS=built, and then deploys or stops per on_complete.

review <slug> — planning side

  1. Require STATUS=built (else: "handoff <slug> is <status> — nothing to review yet").
  2. Read COMPLETION.md → extract Diff range = <base>..<head>.
  3. Invoke Skill with skill: audit and args: "<base>..<head> level=3" (level=5 when the originating triage flow in HANDOFF.md was scientific or security). The audit dispatches the matching domain specialist reviewers over the second session's diff.
  4. On audit clean pass → fire the deploy gate (AskUserQuestion — Run /hyperflow:deploy? Yes / No, binary, no marker). On NEEDS_FIX → the audit fix-gate (Yes → /hyperflow:plan → /hyperflow:dispatch) handles it.
  5. Set STATUS=reviewed once the review is accepted.

complete <slug>

Mark the lifecycle done: set STATUS=reviewed (if not already) and archive the package to .hyperflow-handoff/.archive/<slug>/. Commit chore(handoff): archive <slug>.

Resolution

  • Default <slug> = the most-recently-modified package when omitted from status/pickup/review.
  • A package whose STATUS=planned is a build-side task (run pickup); built is a review-side task (run review). The session-start hook surfaces the right verb automatically.

Iron rules

  • Never edit the build's commits. review is read-only over the diff range; fixes flow through the audit fix-gate → scope → dispatch, never by amending the second session's commits.
  • Never force-push; never --no-verify. Auto-push failures surface the exact git push -u origin <branch>.
  • No AI attribution in any commit or package file.
  • Honors handoff.* config (autoPush, remote, packageDir).

Doctrine

Shared rules in ../hyperflow/DOCTRINE.md. Package contract + templates in ../hyperflow/session-handoff.md.

Frequently asked questions

What does the Handoff AI skill do?

Use when managing a two-session handoff — inspecting, picking up, or reviewing a committed handoff package produced by a session=two scope run. The operator interface over the cross-environment handoff lifecycle (plan in one session, build in another, review back in the first). Trigger with /hyperflow:handoff, "list handoffs", "pick up the handoff", "review the handoff build".

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/jeremylongshore/tons-of-skills-marketplace/tree/main/plugins/ai-agency/hyperflow/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 jeremylongshore 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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