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Dev Commit

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codeaholicguy
dev-commit

AI DevKit · Safe git commit workflow for AI coding agents. Use when the user asks to commit, prepare a commit, stage changes, create a PR-ready checkpoint, or finish work with a conventional commit while avoiding unrelated user changes.

Overview

Publishercodeaholicguy
Repositoryai-devkit
Skill namedev-commit
Stars
1.6K
Forks
252
Bundled files
1
LicenseApache-2.0
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.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

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

Installation

Install the Dev Commit 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/codeaholicguy/ai-devkit.git /tmp/ai-devkit
mkdir -p .claude/skills
cp -r /tmp/ai-devkit/skills/dev-commit .claude/skills/dev-commit
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Dev Commit 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 Dev Commit 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 Dev Commit 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.

Dev Commit

Make one intentional, verified commit without sweeping in unrelated work.

Commit Contract

  1. Check repository state with git status --short --branch, git diff --stat, and git diff.
  2. Identify the files that belong to the requested change. Treat pre-existing user edits, local config, generated artifacts, dependency caches, build outputs, and unrelated formatting churn as out of scope unless the user explicitly includes them.
  3. Run appropriate validation before committing. Prefer the repo's targeted tests, lint, typecheck, build, or documented verification commands. Record skipped validation with the reason. In workspaces whose packages resolve against built artifacts, ensure install and build have run in that worktree (npm ci, npm run build) before full validation or commit hooks; a fresh worktree with stale artifacts fails hooks for environmental reasons.
  4. Stage only intended paths. Prefer explicit pathspecs such as git add path/to/file over git add ..
  5. Re-check with git diff --cached --stat, git diff --cached, and git status --short.
  6. Write a concise conventional commit message: <type>(optional-scope): <summary>.
  7. Commit, then report the commit SHA, final status, validation commands, and any unstaged/untracked files left behind.

Guardrails

  • Do not commit secrets, credentials, .env files, local machine config, caches, coverage, logs, screenshots, or generated files unless the change explicitly requires them.
  • Do not stage another person's unrelated edits. If intended and unrelated changes are mixed in one file, use an interactive or patch-based staging flow and review the staged diff carefully.
  • Do not amend, rebase, force-push, reset, or delete branches unless the user explicitly asks for that operation.
  • If validation fails, stop before committing unless the user explicitly instructs you to commit with failing validation. Report the failing command and key output.
  • If the repo has commit hooks, let them run. If a hook changes files, inspect and stage only intended hook outputs before retrying. If a hook fails, first rule out environmental causes (missing install, stale workspace build artifacts, concurrent test runs sharing resources) by re-running the failing package in isolation; do not treat an environmental failure as a code regression or "stop" condition until isolated runs still fail.

Message Style

Use semantic or conventional commit types that match the change:

  • feat: user-facing feature or capability
  • fix: bug fix
  • docs: documentation-only change
  • test: test-only change
  • refactor: behavior-preserving code restructuring
  • chore: maintenance, build, tooling, metadata, or generated index updates

Keep the subject under about 72 characters when practical, imperative, and specific. Add a body only when it explains non-obvious validation, risk, migration, or follow-up context.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Dev Commit AI skill do?

AI DevKit · Safe git commit workflow for AI coding agents. Use when the user asks to commit, prepare a commit, stage changes, create a PR-ready checkpoint, or finish work with a conventional commit while avoiding unrelated user changes.

Why use Dev Commit on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/codeaholicguy/ai-devkit/tree/main/skills/dev-commit. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Dev Commit?

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 Dev Commit?

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

Is the Dev Commit AI skill free?

Yes. It is published on GitHub by codeaholicguy under the Apache-2.0 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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