gac: an LLM commit message generator with 35+ provider backends
Intelligent LLM-powered git commit message generator that understands your code! Supports multiple languages!
At a glance
- What is it?
- gac replaces git commit -m with a model-generated message drawn from your staged diff. The provider list is unusually long and the interactive loop is well specified, but the README leaves the prompt construction, diff truncation and error handling undocumented, so the quality of any given message is something you have to judge per repository.
- Who is it for?
- Adopt gac if you already have an API key for one of the listed providers and you want commit messages generated from the staged diff without writing your own prompt plumbing; the interactive r, e and free-text feedback loop is the part that makes it usable day to day.
- Can I use it commercially?
- Yes. MIT is a permissive licence: you can use, modify and sell software built on it, as long as you keep its copyright and licence notices.
- Is it still maintained?
- Yes. The repository last received commits 19 days ago.
- What is it written in?
- Mainly Python, according to GitHub's language statistics.
Answers come from the project's GitHub data, last synced on September 15, 2026, and from our analysis. They are not legal advice.
DEEP OPEN-SOURCE ANALYSIS
The problem gac targets, and who actually has it
Writing a commit message is a small tax that compounds. The README frames the tool as a direct replacement for git commit -m "..." and the Quick Start reduces the whole workflow to two commands: uvx gac init to configure a provider, model and language, then uvx gac to generate and commit. The audience is developers who already commit frequently and who already have access to a language model, either through an API key or through a local runtime. The provider list is the clearest signal of that audience: it spans hosted APIs (Anthropic, OpenAI, Gemini, Mistral AI, DeepSeek, Groq, Together AI), aggregators (OpenRouter, Plexus Gateway), local runtimes (Ollama, LM Studio), and OAuth flows for tools people already pay for (ChatGPT, Claude Code, GitHub Copilot). That breadth matters because it means gac does not force a new subscription on you. If you already run Ollama locally, the marginal cost of generating a message is zero and nothing leaves the machine. If you already have a Copilot or Claude Code seat, the README suggests those OAuth paths are supported rather than requiring a separate API key. The tool is not aimed at teams that enforce a hand-written changelog, and it is not aimed at anyone who wants a deterministic, reviewable mapping from diff to message.
What the interactive loop does between diff and commit
The mechanism visible in the README is a generate, review, confirm cycle rather than a fire-and-forget hook. You stage changes, run uvx gac, and the tool produces a candidate message. Before anything is written, you get three responses: y to accept, r to reroll and get a different message from the same diff, and e to edit. Editing opens an in-place TUI by default, or your $GAC_EDITOR if that variable is set. There is a fourth path that is more interesting than the other three: you can type free-text feedback such as "make it shorter" or "focus on the bug fix" and the model regenerates against that instruction. That turns the commit step into a short conversation rather than a single shot, and it is the part of the design most likely to determine whether the tool survives past the first week. Two flags change the shape of the output. -o produces a single-line conventional-commit message. -v produces a longer explanation covering motivation, technical approach and impact. A separate --50-72 flag enforces the classic subject and body width convention, and --signoff appends a Signed-off-by line for DCO compliance, which the README notes is required by projects including Cherry Studio and the Linux kernel. The --interactive (-i) flag goes further and asks you targeted questions about the changes before generating, which is a way of supplying context the diff alone does not carry. What the README does not describe is how the diff is assembled or truncated before it reaches the provider, and that omission matters more than any of the flags above.
Grouping, hooks and the MCP server
Three features sit outside the basic generate-and-commit path. The first is --group, which the README describes as automatically grouping related changes into multiple logical commits. This is the most consequential flag in the tool, because it means gac can decide to split your working tree into several commits rather than one. The README does not explain the grouping heuristic, whether it operates on file paths, hunks or model judgement, or what happens when the grouping is wrong and you have already accepted it. Treat that as an area to test deliberately rather than a feature to enable by default. The second is hook integration: the README states that gac respects pre-commit and lefthook hooks and runs them before the expensive LLM operation. That ordering is the right one, since a failing linter should stop the process before you spend tokens, but it also means a slow hook delays the message rather than the commit. The third is uvx gac serve, which exposes commit tools to AI agents over the Model Context Protocol. That is a different use case from the interactive CLI: it lets an agent that is already editing files produce commits through the same generator. If you are not running an MCP-capable agent, this command is irrelevant to you, and the README does not document which tools the server exposes or what permissions it assumes.
Installation and the configuration surface
The README's Quick Start assumes uv and does not present a pip path, though the project publishes to PyPI as gac. The two commands given are uvx gac init and uvx gac. The init step is described as configuring your provider, model and language, and it also asks whether to enable usage statistics, with the README stating that it explains exactly what is stored at that point. Language has a second entry point: uvx gac language sets a default, while the -l <language> flag overrides it for a single run. The README claims 25+ languages and notes that conventional commit prefixes can either stay in English for tool compatibility or be translated along with the rest of the message. That choice is worth making consciously, because a translated prefix breaks parsers that expect feat: or fix:. Statistics are a separate command family: uvx gac stats for an overview, stats models, stats projects and stats recent for breakdowns, stats reset for a full wipe and stats reset model <model-id> for a single model. The storage location is given as ~/.gac_stats.json and the README is explicit that only counts, dates, project names and model names are kept, with no commit messages, code or personal data, and no telemetry. Disabling is a single environment variable, GAC_DISABLE_STATS, which accepts true, 1, yes or on to turn stats off, and false, 0 or no to leave them on. The editor override is GAC_EDITOR. Those are the only configuration keys the supplied material names.
Where the documentation stops being useful
The README is a feature list, and feature lists are silent about failure. Nothing in the supplied material describes how the staged diff is prepared before it is sent, whether large diffs are truncated, chunked or rejected, what token ceiling applies, or how conflicts between the diff and the instruction are resolved. For a tool whose entire output is a model response conditioned on your code, that is the central undocumented behaviour. There is also no statement about retry behaviour when a provider returns an error, no rate-limit handling, and no description of what gac does when the model returns a malformed message or an empty one. The secret detection feature is mentioned in the feature list but the supplied text is truncated mid-sentence at "Scans for API keys, passwords, and tokens before c", so the scope of that scan, whether it blocks the commit or only warns, and which patterns it covers cannot be confirmed from this material. Do not treat that bullet as a guarantee that a credential in your diff will be caught. The provider count is likewise a claim rather than a verified list: the README enumerates names, but which of them are maintained, tested in CI, or usable without a paid account is not stated. The repository does carry CI, codecov, Ruff and mypy badges, which indicates type checking and linting are part of the project's own process, but that says nothing about whether a given provider integration is exercised on every push.
How gac differs from a commit-msg hook or a hand-written template
The obvious alternative is not another LLM tool but the conventional commit-msg hook, which validates a message you wrote rather than generating one. The difference in approach is where the judgement lives. A hook encodes rules: a regex for the subject line, a length limit, a required ticket reference. It is deterministic, it costs nothing per commit, and it cannot invent a claim about your change that is not true. gac moves the judgement to a model that reads the diff, which is why it can produce the "why" the README advertises, and also why it can produce a confident sentence that misdescribes what you did. The two are not mutually exclusive: gac's --50-72 and --signoff flags exist precisely because teams already have format rules, and a commit-msg hook running after gac would catch a generated message that violates them. The second alternative is writing the prompt yourself against a provider SDK. gac's value there is the plumbing: 35+ provider integrations, OAuth paths for ChatGPT, Claude Code and GitHub Copilot, an editor handoff, a reroll loop, and stats. If you need control over exactly what text is sent, building on the SDK gives you that and gac, per its README, does not document it. Choose gac for the integration surface, not for the prompt.
Maintenance cost, licence and what to check before adopting
The project is MIT licensed, which permits commercial and private use and modification, and the licence file is linked from the README. This is a summary of what the licence identifier means, not legal advice; if you are redistributing gac inside a product, read the LICENSE file and your own counsel's view. On maintenance, the supplied metadata shows three releases in 2026: v3.16.0 on 2026-04-27, v3.18.0 on 2026-04-30 and v3.26.0 on 2026-05-06, with a last push of 2026-08-28 and the repository not archived. That release cadence over roughly ten days suggests active iteration, and the version jump from 3.18 to 3.26 in six days is a hint that the surface is still moving. Practically, that means pinning matters. If you install via uvx without a version constraint you are tracking the latest release, and a flag or a provider default can change under you. The upgrade cost is otherwise low: there is no server, no database and no schema, just a CLI and a local JSON stats file at ~/.gac_stats.json that you can delete or disable with GAC_DISABLE_STATS. The ongoing cost that is easy to overlook is the per-commit API spend on hosted providers, which the README does not estimate and which depends entirely on your diff sizes and chosen model. Run gac stats models after a week if you enable stats, since the README states it reports tokens and latency per model, and that is the only cost signal the tool itself gives you.
Editorial conclusion
Adopt gac if you already have an API key for one of the listed providers and you want commit messages generated from the staged diff without writing your own prompt plumbing; the interactive r, e and free-text feedback loop is the part that makes it usable day to day. Do not adopt it if your repository contains secrets you cannot reliably exclude, if you need a published specification of how the diff is trimmed before it reaches the provider, or if you are unwilling to pay per commit on a hosted model. Verify three things first: run uvx gac init and confirm the provider you intend to use appears in the list, check whether stats are enabled and whether ~/.gac_stats.json is acceptable on the machine, and make one commit in a scratch repository to see the message quality before wiring it into a real one.
Community notes