gitl

AI-powered git history reviewer for CLI and CI. gitl (git-log-lens) reads a repository's git history and turns it into a structured engineering artifact via LLM:

• gitl review <range> — AI review of a commit range / PR with machine-readable risk scoring (low|medium|high) for CI gating (--fail-on=high → non-zero exit code); streams tokens to the terminal in real time; on-disk LLM response cache; custom system-prompt templates.
• gitl changelog [<range>] — Keep a Changelog-style changelog, grouped by conventional commits (defaults to last tag → HEAD);
• gitl digest [--days=N] [--repos=a,b,c] — activity summary by author/topic/file, including multiple repositories in parallel; interactive TUI viewer (--tui).

A clean CLI binary plus a GitHub Action wrapper — no server, no database, no hosted key storage. BYOK (bring your own key) with multi-provider support: OpenAI-compatible API, Ollama (local/self-hosted), Azure OpenAI. No telemetry.

Status: v0.3.1 released — all three commands work on real repositories with all three output formats (md|text|json). The Action posts AI reviews as sticky PR comments and gates on risk score. Release binaries are cross-compiled, cosign-signed, and covered by SLSA L3 build provenance (see VERIFY.md).

Quick start

Requires Go 1.22+ and git in PATH.

# build
go build ./...

# AI review of a commit range — streams tokens to the terminal in real time
GITL_API_KEY=sk-... go run ./cmd/gitl review HEAD~5..HEAD

# no key = deterministic offline review (heuristic risk, no network call)
go run ./cmd/gitl review HEAD~5..HEAD

# machine-readable output for CI + risk gating
go run ./cmd/gitl review HEAD~5..HEAD --format=json
go run ./cmd/gitl review HEAD~5..HEAD --fail-on=high   # non-zero exit on high risk

# estimate cost without making an API call
go run ./cmd/gitl review HEAD~5..HEAD --dry-run

# custom system-prompt template (e.g. your team's review policy)
go run ./cmd/gitl review HEAD~5..HEAD --system-template=./review-policy.md

# skip the on-disk LLM cache (always call the model)
go run ./cmd/gitl review HEAD~5..HEAD --no-cache

# disable streaming (non-interactive, buffered output)
go run ./cmd/gitl review HEAD~5..HEAD --no-stream

# changelog from last tag (or full history if no tags) — no LLM
go run ./cmd/gitl changelog
go run ./cmd/gitl changelog v1.2.0..HEAD --format=json

# activity summary for the last N days — no LLM
go run ./cmd/gitl digest --days=14

# multi-repo digest: runs in parallel; one unreachable repo does not fail the rest
go run ./cmd/gitl digest --repos=../service-a,../service-b --format=json

# interactive TUI viewer for digest (requires a TTY)
go run ./cmd/gitl digest --days=14 --tui

go run ./cmd/gitl version
go run ./cmd/gitl --help

# tests
go test ./...

Install:

# Go toolchain
go install github.com/akomyagin/gitl/cmd/gitl@latest

# Homebrew (macOS/Linux)
brew install akomyagin/tap/gitl

# Or download a signed release binary from GitHub Releases (see VERIFY.md)

Local multi-provider test (Ollama)

docker-compose.yml starts only the dev dependency — a local Ollama instance for testing the multi-provider LLM client (gitl itself is not containerized):

docker compose up ollama

Configuration

Two levels, merged by priority: flag > env > .gitl.yaml (repo) > ~/.config/gitl/config.yaml (personal). The repo-level .gitl.yaml is committed as a shared team policy (risk threshold, excluded paths, changelog categories). Without a key, gitl runs in deterministic offline mode.

In offline mode — or when a real model omits a valid risk block and gitl falls back to the heuristic — the risk header is annotated with *(heuristic)* (and "heuristic": true in --format=json), so a deterministic score is never mistaken for a model's own judgement.

Providers (llm.provider)

# OpenAI-compatible API (default)
llm:
  provider: "openai"
  api_key: ""            # or env GITL_API_KEY
  base_url: "https://api.openai.com/v1"
  model: "gpt-4o-mini"

# Ollama — local/self-hosted, no key, free
llm:
  provider: "ollama"
  base_url: "http://localhost:11434/v1"
  model: "llama3.1"

# Azure OpenAI — custom auth/endpoint format
llm:
  provider: "azure_openai"
  api_key: ""             # or env GITL_API_KEY
  model: "gpt-4o-mini"    # used only for cost estimation
  azure_openai:
    endpoint: "https://<resource>.openai.azure.com"
    deployment: "<deployment-name>"
    api_version: "2024-08-01-preview"

Streaming (output.stream)

When reviewing interactively (md or text format on a TTY), gitl streams tokens to the terminal as they arrive — no waiting for the full response. Streaming is on by default and switches off automatically in CI (non-TTY stdout) or with --format=json.

output:
  stream: true   # default; set false to always buffer

Disable per-call: gitl review HEAD~5..HEAD --no-stream

LLM response cache (cache)

gitl review caches model responses on disk (SHA-256 of provider + model + prompt). Identical diffs reuse the cached result instantly, with no API call or cost.

cache:
  enabled: true    # default
  ttl_hours: 24    # entries older than this are ignored

Cache lives in ~/.cache/gitl/review/ (XDG-compliant). Disable per-call: gitl review HEAD~5..HEAD --no-cache

Custom templates (output.system_template)

Supply your own system prompt to steer the model's review focus — security checklist, architecture constraints, team-specific rules:

output:
  system_template: "./review-policy.md"   # path relative to CWD

Override per-call: gitl review HEAD~5..HEAD --system-template=./my-policy.md

The template has access to {{ .Commits }}, {{ .Diff }}, {{ .RepoName }} and the full set of template functions documented in internal/prompt/templates.go.

GitHub Action

gitl can be wired up as a GitHub Action: it AI-reviews a pull request's commits and posts a comment with the risk score, optionally blocking merge above a threshold. The Action builds gitl from source (go install at a pinned version).

Add .github/workflows/gitl-review.yml to your repository:

name: gitl review
on:
  pull_request:

permissions:
  contents: read          # for checkout
  pull-requests: write    # to post the review comment

jobs:
  review:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4
        with:
          fetch-depth: 0    # required: without full history base..head won't resolve

      - uses: akomyagin/gitl@v0.3.1
        with:
          gitl-api-key: ${{ secrets.GITL_API_KEY }}   # BYOK, see below
          fail-on: high                               # optional: block merge on high risk

Security best practices:

• Key via secrets.* only. gitl-api-key comes from secrets.GITL_API_KEY (set under Settings → Secrets and variables → Actions), never hardcoded in YAML or committed. If the secret is not set, the Action runs in deterministic offline mode (no network, no cost).
• Minimal permissions:. Only pull-requests: write (posting the comment) and contents: read (checkout) are needed — do not grant broader rights.
• fetch-depth: 0 is required. GitHub provides base/head SHAs in the pull_request event, but a shallow clone won't resolve base.sha..head.sha.
• fail-on defaults to never. The Action only comments; it does not block merges unless you opt in explicitly (fail-on: high, etc.) — same "WARN by default, hard gate is explicit opt-in" principle as the CLI (--fail-on).
• Diff privacy. In CI, the diff is sent to whichever LLM provider is configured (default: OpenAI-compatible API). For private code, use a self-hosted/enterprise provider (Ollama, Azure OpenAI) — see Providers above.
• Secret masking. GitHub automatically masks secrets.* values in runner logs as ***, but that's not a reason to print the key in your own workflow steps.

License

MIT.