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GitReins

Git-Native Agent Co-Harness — static guards + agentic evaluator for AI-assisted code

CI Python 3.10+ License: MIT PyPI

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GitReins lives inside your git repository as a quality harness. It provides MCP tools for task lifecycle management, an agentic evaluator that judges code completeness against task definitions, and git hooks that ensure nothing bypasses the quality gates.

✅ v0.12.0 — LSP diagnostics (14 languages), opt-in static analysis (9 analyzers, default off), commit audit with CVE-scored severity, optional Antares CVE-localization guard, Anthropic Messages API support, DeepSeek prompt caching telemetry, large-repo hardening (fast-track + --skip-tier2), MCP propagate, judge single-flight + resume lease, evaluator committed-diff read path, 1335 tests pass / 32 test files, verified on a full run 2026-08-25 (1328 passed, 7 skipped, 1 known env-dependent LSP flake — tracked at tests/test_lsp.py PYLSP_SKIP_310).


Quick Start

pip install gitreins
cd /path/to/your-project
gitreins install        # creates .gitreins/config.yaml + pre-commit hook
gitreins init           # smart init — detects language, size, optimal config

Running from a source checkout (no pip install): the gitreins console script is not on your PATH — it lives in the repo's virtualenv. Activate it first in each shell, then the commands above work as written:

source .venv/bin/activate        # or call .venv/bin/gitreins directly
gitreins --help

New to GitReins? Read the Onboarding Guide — full install → init → first guard run → task workflow, plus troubleshooting for the most common first-run failures (gitleaks regex config, Python import setup).

uv is optional. gitreins init prefers uv run pytest as the test command when uv is installed, but a machine without uv still passes the tests guard: when the configured test_command starts with a runner (uv run / pipenv run / poetry run) whose binary is missing from PATH, the guard automatically falls back to python -m pytest ... and prints a warning line. pip-only users never see uv: command not found.

How It Works

  1. Create tasks — Define criteria via CLI or MCP tools
  2. Work with your AI agent — Claude, Hermes, Codex, or Pi does code generation
  3. Complete tasks — gitreins task complete <id> triggers automatic evaluation
  4. Tier 1: Static guards — secrets, build, lint, tests (configurable)
  5. Tier 2: Agentic evaluator — LLM loop reads files, runs tests, delivers per-criterion PASS/FAIL
  6. Verdicts persisted — stored in .gitreins/history/, browsable via gitreins report
  7. Commit through harness — pre-commit hook runs guards, blocks if checks fail

MCP commit rule: the MCP commit tool refuses while any task is in_progress — completed work must be judged against the task's criteria first. Finish tasks with task.complete (which runs the quality judge) or remove them with task.delete, then retry the commit.

Commands

gitreins install                      # Install hooks + config
gitreins init                         # Smart init (language, size, optimal config)
gitreins guard [--dead-code]          # Run Tier 1 static checks (--dead-code: opt-in Python dead-code detection)
gitreins security-scan [-d DIR] [--output text|json] [--force-ml]
                                       # Run the Antares CVE localization scanner
gitreins report [-n N] [--interactive]  # Browse verdict history
gitreins task create <id> <title> [criteria...] [--depends-on ...]
gitreins task start <id>
gitreins task complete <id> [--force]
gitreins task list [--status pending|in_progress|complete]
gitreins task delete <id>
gitreins judge <id>                   # Evaluate a task
gitreins commit <message>             # Commit with guard checks
gitreins commit-audit [message]       # Validate commit message against staged diff (commit-msg hook)
gitreins setup-tools                  # Show available static analysis tools and install instructions
gitreins mcp-server                   # Run MCP stdio server (for AI agents)

Security Scan (optional)

GitReins ships an opt-in Tier 1 security guard that localizes known CVEs against your staged Python code. It is built on the Antares CVE localization framework (FDTN-AI's 1B-parameter model fine-tuned for code-level vulnerability localization). Until the optional ML stack is installed, the guard falls back to a keyword-based heuristic that produces CVE-SIMULATED findings so the wiring can be exercised end-to-end.

CLI

# Scan staged Python files (default; used by `gitreins guard`).
gitreins security-scan

# Recursively scan a directory instead of staged files.
gitreins security-scan --directory engine/

# Machine-readable output for piping into other tools.
gitreins security-scan --output json

# Require real ML inference — fail if huggingface_hub/transformers
# are not installed (exit code 2). Without this flag the heuristic
# fallback is used.
gitreins security-scan --force-ml

Exit codes:

Code Meaning
0 Clean — no findings
1 One or more findings produced
2 --force-ml requested but ML dependencies are missing

Install requirements

The heuristic scanner has no extra dependencies. Real ML inference requires the optional ML stack:

pip install huggingface_hub transformers
# Optional, for GPU inference:
pip install torch        # or onnxruntime

The model is downloaded on first use into ~/.cache/gitreins/antares-1b/ and reused on subsequent runs.

Configuration

Enable the guard in .gitreins/config.yaml:

defaults:
  security_scan:
    enabled: true              # opt-in: default false
    model: antares-1b          # "antares-1b" | "antares-350m"
    min_confidence: 0.7        # filter by CVSS severity score
    cve_source: nvd            # "nvd" | "github" | "both"
Key Default Notes
enabled false When true, the security_scan guard runs alongside other Tier 1 checks
model antares-1b HuggingFace model id; antares-350m is a smaller variant
min_confidence 0.7 Drop entries whose CVSS score is below this. Severity→score: CRITICAL=1.0, HIGH=0.85, MEDIUM=0.6, LOW=0.3
cve_source nvd nvd uses the NVD REST API, github uses the GitHub Advisory Database, both merges the two

The CVE feed is cached at ~/.cache/gitreins/cve_feed/ with a 24-hour TTL. When the network is unreachable the feed serves stale cache; when both cache and network are unavailable the feed returns an empty list and the guard exits clean (it is opt-in and must never block a commit on missing infrastructure).


Test Modes: full vs diff

GitReins supports two strategies for when tests run on commit, controlled by test_mode in .gitreins/config.yaml.

test_mode: "full" (default for new projects)

The entire test suite runs on every commit. Safe and thorough.

Best for:

  • New projects with a small, fast test suite
  • Projects where all tests pass reliably
  • When you want maximum safety on every commit

Tradeoff: Slow on large projects. Pre-existing failures in untouched code block unrelated commits.

guards:
  test_mode: "full"

Only tests for packages you actually changed. Uses basename mapping:

Changed file Test run
engine/guard_manager.py tests/test_guard_manager.py
gitreins/cli.py tests/test_cli.py
gitreins_mcp/server.py tests/test_mcp_server.py

Best for:

  • Projects with 5+ packages where full suite is slow
  • Projects with pre-existing test failures in untouched code
  • When you want fast feedback on the code you actually changed

Safety nets — diff mode falls back to full suite when:

  • pyproject.toml, .gitreins/config.yaml, Makefile, or setup.cfg changed
  • A test file itself changed (always included, plus its source-mapped siblings)
  • Changed files don't map to any known test files (unknown file = safety)
  • No staged files at all
  • Test command isn't pytest (custom runners can't be narrowed)

Tradeoff: Less safety on cross-cutting changes. Config changes always trigger full suite.

guards:
  test_mode: "diff"

Which mode should I use?

Project state Recommended mode
Brand new, <5 packages full
Mature, 5+ packages, tests pass diff
Mature, pre-existing test failures diff
Refactoring across packages full (temporarily)
CI / PR checks full (safety over speed)

Output examples

Full mode:

Tier 1 Guards: PASS  (test mode: full)
  ✓ secrets — clean
  ✓ lint — ok
  ✓ tests — passed

Diff mode (targeted):

Tier 1 Guards: PASS  (test mode: diff, 3 test file(s))
  ✓ secrets — clean
  ✓ tests — passed

Diff mode (safety trigger — full suite):

Tier 1 Guards: PASS  (test mode: diff, full suite — safety trigger)
  ✓ secrets — clean
  ✓ tests — passed

Verdict History

Every gitreins task complete and gitreins judge saves a verdict to .gitreins/history/. Configure in .gitreins/config.yaml:

history:
  enabled: true              # false = don't save verdicts
  storage: "git"             # "git" = auto-commit to gitreins branch
                             # "filesystem" = write files only, no git commits
  max_verdicts: 1000         # auto-prune old entries

Browse history:

gitreins report              # last 10 evaluations
gitreins report -n 20        # last 20
gitreins report --interactive  # TUI with arrow-key navigation (requires textual)

Branch mechanics (git storage)

With storage: "git" (the default), every verdict is auto-committed to a dedicated orphan gitreins branch — never to main. The branch is only checked out transiently (or updated via a temporary worktree), so your working tree is never disturbed. .gitreins/history/ is intentionally gitignored: the verdict files are runtime artifacts whose canonical home is the gitreins branch, and a fresh clone therefore has no local .gitreins/history/ directory.

gitreins report reads verdicts in this order:

  1. Local filesystem — .gitreins/history/ in the working tree (used when present, e.g. right after a judge run in the same checkout).
  2. gitreins branch fallback — when the local directory is missing or empty and storage is "git", verdicts are read straight from the branch (git ls-tree / git show), so a fresh clone can still browse the full verdict history.

To inspect the branch directly:

git log --oneline gitreins                                            # verdict commits
git ls-tree -r --name-only gitreins -- .gitreins/history              # stored files
git show gitreins:.gitreins/history/<date>/<hash>/verdict.json        # one verdict

With storage: "filesystem", verdicts are written locally only — no branch is created and the fallback is skipped.

Task Dependencies

Tasks can depend on other tasks. Evaluation is blocked until dependencies pass:

gitreins task create build "Project builds" \
  "CGO_ENABLED=0 go build ./cmd/server exits 0"

gitreins task create api-crud "CRUD endpoints" --depends-on build \
  "POST /api/users creates a user" \
  "GET /api/users lists users"

gitreins task complete api-crud
# → "Cannot complete 'api-crud' — depends on: build"

gitreins task complete build      # complete the dependency first
gitreins task complete api-crud   # now this works

# Or force-skip dependency checks:
gitreins task complete api-crud --force

Configuration

Full .gitreins/config.yaml reference:

# ── Global defaults ──────────────────────────────────
defaults:
  model: deepseek-v4-flash
  max_iterations: 100
  check_for_updates: true

# ── Tier 1 guards ────────────────────────────────────
guards:
  secrets: true
  lint: true
  tests: true
  test_mode: "full"          # "full" or "diff"
  # uv/pipenv/poetry are OPTIONAL — if the runner prefix's binary is not on
  # PATH, the guard falls back to `python -m pytest ...` with a warning.
  test_command: "uv run pytest -x --tb=short"

  # Go projects (auto-detected via go.mod):
  go:
    build: true
    lint: true
    tests: true

# ── Tier 2 evaluator caps ────────────────────────────
evaluator:
  max_iterations: 25         # LLM reasoning turns
  max_time: "5m"             # wall clock cap
  max_input_tokens: "200k"
  max_output_tokens: "50k"
  tool_call_weight: 0.1      # tool calls cost 0.1 iterations

# ── Verdict history ──────────────────────────────────
history:
  enabled: true
  storage: "git"
  max_verdicts: 1000

Tech Stack

  • Language: Python 3.10+
  • Dependencies: mcp, pyyaml, requests, packaging (4 packages)
  • MCP Transport: stdio (12 tools)
  • Config: YAML in .gitreins/ directory
  • Evaluator Default Model: DeepSeek V4 Flash (~$0.01/eval)
  • Test suite: ~1335 tests across 32 test files (parallelized with pytest-xdist; last verified full run 2026-08-25: 1328 passed, 7 skipped, 1 known env-dependent LSP flake — tracked at tests/test_lsp.py PYLSP_SKIP_310)

Architecture & Docs

Document What it covers
Full Architecture System design and data flow
Component Map Module inventory with paths and line counts
Agentic Evaluator Design How the evaluator loop works

License

MIT

Metadata

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