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Git Master

Community
Dark-Alex-17
git-master

Methodology for atomic commits, rebase surgery, and clean git history. Grants shell access for running git commands.

Overview

PublisherDark-Alex-17
Repositorycoyote
Skill namegit-master
Stars
56
Forks
2
Bundled files
Instructions only
LicenseAGPL-3.0
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 Dark-Alex-17 on GitHub. Read the source before you install it.

Installation

Install the Git Master 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/Dark-Alex-17/coyote/tree/main/assets/skills/git-master
  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/Dark-Alex-17/coyote.git /tmp/coyote
mkdir -p .claude/skills
cp -r /tmp/coyote/assets/skills/git-master .claude/skills/git-master
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Git Master 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 Git Master 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 Git Master 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.

You are operating on a git repository. Apply these conventions strictly. Use the git_command tool to run git commands.

Atomic commits

Each commit represents one logical change. If the commit message needs the word "and," the change is too large; split it. Mixed concerns in one commit are nearly impossible to revert cleanly later.

Commit messages

  • Subject line: imperative mood, ≤50 characters, no trailing period.
  • Blank line.
  • Body: explain WHY, not WHAT. The diff shows what changed.
  • Reference issues by URL or canonical ID, not by free-form description.

Rebase, don't merge

  • git rebase -i origin/main before opening a PR.
  • Squash WIP commits and fixups; keep only meaningful commits in the final history.
  • Never rebase a branch others may have based work on. If unsure, ask.

Conflict resolution

  • Read both sides carefully before resolving. Don't reflexively take "ours" or "theirs."
  • After resolving, run tests before continuing the rebase.
  • For non-trivial conflicts, document the resolution choice in the resulting commit body.

Investigation workflow

Use git_command to run these inspection commands when chasing down history:

  • git log -p <file> — see how a file evolved over time.
  • git log -S '<string>' (pickaxe) — find when a string was added or removed.
  • git log --all --grep '<pattern>' — search commit messages.
  • git blame -L <start>,<end> <file> — current authorship for a line range.
  • git diff <ref1>..<ref2> -- <path> — narrow diffs to specific paths.
  • git bisect start && git bisect bad && git bisect good <ref> — narrow down regressions.

Safety checklist before destructive operations

Before running anything that rewrites history or deletes refs:

  • git status — confirm clean working tree.
  • git branch --show-current — confirm which branch you're on.
  • git log -3 --oneline — confirm what's about to be moved.

Worktrees

A worktree is an ephemeral workspace: it lives exactly as long as the work that needed it.

  • Create under one dedicated directory (e.g. .worktrees/<name>), never nested inside another worktree.
  • Remove it the moment the work lands or is abandoned — git worktree remove <path> (--force when it holds discarded changes). Stale worktrees accumulate silently, hold branch checkouts hostage (a branch checked out in any worktree can't be checked out or deleted elsewhere), and confuse later automation.
  • git worktree list before creating one (collisions) and after finishing a batch of work (no strays). git worktree prune after any manual directory deletion.
  • Removing a worktree never deletes its branch — decide branch retention separately, on purpose.
  • Never remove the worktree you are standing in; step out (or have the parent checkout do it).

What to never do

  • Force-push to shared branches (main, release branches, anything teammates pull from).
  • git reset --hard without confirming current branch and verifying the reflog can recover.
  • git push --no-verify to skip hooks — fix the underlying issue instead.
  • Commit secrets, even temporarily. Once pushed, treat as compromised; rotate.

When unsure, read state first

Before guessing at a fix, run git status, git log -5 --oneline, and git diff (or git diff --staged) to see the actual state. Don't operate on assumptions.

Frequently asked questions

What does the Git Master AI skill do?

Methodology for atomic commits, rebase surgery, and clean git history. Grants shell access for running git commands.

Why use Git Master on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Dark-Alex-17/coyote/tree/main/assets/skills/git-master. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Git Master?

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 Git Master?

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

Is the Git Master AI skill free?

Yes. It is published on GitHub by Dark-Alex-17 under the AGPL-3.0 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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