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Prepare Paperclip Pr

OrganizationPopular
paperclipai
prepare-paperclip-pr

Prepare a Paperclip branch for PR with commits, template body, and checks.

Overview

Publisherpaperclipai
Repositorypaperclip
Skill nameprepare-paperclip-pr
Stars
95.4K
Forks
16.2K
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 paperclipai on GitHub. Read the source before you install it.

Installation

Install the Prepare Paperclip Pr 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/paperclipai/paperclip/tree/master/.agents/skills/prepare-paperclip-pr
  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/paperclipai/paperclip.git /tmp/paperclip
mkdir -p .claude/skills
cp -r /tmp/paperclip/.agents/skills/prepare-paperclip-pr .claude/skills/prepare-paperclip-pr
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Prepare Paperclip Pr 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 Prepare Paperclip Pr 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 Prepare Paperclip Pr 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.

Prepare Paperclip PR

The standard Paperclip procedure for turning branch work into a reviewed, green pull request against paperclipai/paperclip master. Apply it once per PR (if a task splits a branch into several PRs, run the whole procedure for each one).

0. Preconditions — worktree safety

  • Do all PR work in a git worktree on a dedicated branch. The main ~/paperclip checkout typically runs the live Paperclip server — never check out branches there. If you are already on a worktree/branch, verify it (git rev-parse --git-dir, git branch --show-current) and proceed.
  • If the main checkout is unexpectedly off master, fix that first without losing work (usually: move that branch's work into a worktree).
  • Confirm which remote/ref you are targeting (normally master on the paperclipai/paperclip repo; the task may name a specific remote such as origin or public-gh).

1. Commit everything — lose no work

  • Make logical commits of all uncommitted changes before anything else. Do not stash and forget; do not leave files behind. If commits are missing, make them.
  • Commit messages must end with exactly: Co-Authored-By: Paperclip <noreply@paperclip.ing>

2. Get changes cleanly on top of master

  • Fetch the target remote and rebase (or otherwise replay) your branch on top of the target master so the PR has no merge conflicts.
  • Re-verify after rebase: build/tests relevant to the change still pass at whatever depth the task warrants.

3. Guardrails checklist (every PR)

  • Never commit pnpm-lock.yaml — the repo has actions that manage it. If it is already in a commit, rewrite/drop that change before pushing.
  • Never change .github/workflows/* unless the underlying commit was explicitly about that and the task calls it out.
  • No design screenshots / wireframe images committed to the repo unless they are genuinely part of the work product.
  • Migrations: numbered incrementally with no conflicts against master. If master moved and took your number, renumber on top. Make migrations idempotent so users who already applied the old number are safe.
  • Greptile file limit: keep each PR under 100 changed files; if a PR exceeds that, split it into two.

4. Open the PR

5. Review loops

  • Run the /greploop company skill: trigger Greptile review, address its comments, push, and repeat until Greptile gives 5/5 with zero unresolved comments (max 20 turns). Do not stop early while turns remain.
  • Then run the /prcheckloop company skill and address any verification / CI failures you can.
  • RUN GREPTILE UNTIL IT GETS TO 5/5 - DO NOT STOP UNTIL GREPTILE IS 5/5, all tests pass, all verification checks pass, and there are no merge conflicts.

6. Report back and hand off

  • Comment on the driving task: what you did, the PR URL(s), the worktree path (use ~ for home), Greptile score, and check status.
  • Create a pull_request work product for each opened PR (plus branch / commit work products where the branch or a commit is itself the handoff).
  • If the task requires follow-up per PR (e.g. sub-issues per PR), create them as the task directs and link them.

Hard rules

  • Never lose work: no orphaned stashes, no dropped files, no force-pushes that discard commits.
  • Always post the URLs to every pull request you created.

Frequently asked questions

What does the Prepare Paperclip Pr AI skill do?

Prepare a Paperclip branch for PR with commits, template body, and checks.

Why use Prepare Paperclip Pr on TypingMind?

Because you install it once and use it with any model. Prepare Paperclip Pr 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 Prepare Paperclip Pr in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/paperclipai/paperclip/tree/master/.agents/skills/prepare-paperclip-pr. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Prepare Paperclip Pr?

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 Prepare Paperclip Pr?

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

Is the Prepare Paperclip Pr AI skill free?

Yes. It is published on GitHub by paperclipai 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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