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An imitator of yours, A PR review tool like co-maintainer.
It collects current code and workflows, selected pull requests and diffs, and default-branch commits. A low-cost model extracts evidence-bound observations. A higher-reasoning model turns them into concise contribution guidance for implementation, testing, review, and release decisions.
npm install -g co-maintainerRequires Node.js 24 or newer.
co-maintainer probe owner/repo --auth=gh
co-maintainer init owner/repo --auth=gh --ai=openrouter \
--low-model=openai/gpt-oss-120b \
--high-model=openai/gpt-5.6-luna \
--include-codebase --include-pull-requests \
--include-pull-request-changes --include-commit-history \
--include-how-repo-works
co-maintainer review owner/repo 123 --improve-matrix=2 --debug
co-maintainer review # local branch (staged, unstaged, untracked)
co-maintainer review --json # machine-readable stdout, logs on stderr
co-maintainer review --output=github # annotations and a job summary inside GitHub ActionsSettings live in config.json, so a flag you use every time can be saved once:
co-maintainer config set ai openrouter # or openai, anthropic, opencode-zen, opencode-go
co-maintainer config set ai-key sk-or-... # your provider's key (OpenRouter, OpenAI, Anthropic or OpenCode)
co-maintainer config set high-model openai/gpt-5.6-luna
co-maintainer config set low-model openai/gpt-oss-120b
co-maintainer config list # every key, its value and its sourceDocumentation: Getting started
(install to first review) and the full docs site,
sources in docs/md/.
Use co-maintainer help, co-maintainer -h, or co-maintainer --help for the
full CLI help. Every guide the CLI writes is also readable from the dashboard,
and the dashboard keeps its guides separate from the CLI's. See
dashboard.md.
co-maintainer is a new tool, so it has not been compared with many others yet.
It was benchmarked against OCR on core_v2. The
datasets are small, so read the numbers as a signal, not a guarantee.
Claim, as measured on core_v2 |
Result |
|---|---|
| Result quality against OCR | 2 to 3x better |
| Speed against OCR | 2 to 8x faster |
| Tokens per review against OCR | 70 to 200x fewer |
| Cost per review against OCR | 60 to 270x cheaper |
xychart-beta
title "Monthly PR Review Cost by Developer Count"
x-axis [1, 5, 10, 20, 30, 40, 50, 60, 70, 80, 100]
y-axis "Monthly Cost ($)" 0 --> 13000
line "OCR" [129.6, 648, 1296, 2592, 3888, 5184, 6480, 7776, 9072, 10368, 12960]
line "co-maintainer" [2, 10, 20, 40, 60, 80, 100, 120, 140, 160, 200]
Calculated from co-maintainer's core_v2 benchmark, which reports co-maintainer as 65x cheaper per review than OCR ($0.025/review vs. $1.62/review). Assumes 80 PR reviews per developer per month (40 PRs merged, about 2 reviews each).
core_v3 fits co-maintainer's use case better than the OCR comparison, so it is
the more meaningful metric here. Unlike the OCR comparison (real human review
comments as gold, see benchmark/swe-prbench), bench core v3 scores against
deliberately seeded, hand-verified defects in a dedicated target repo. Half of
the PRs are kept as defect-free controls, so precision is measurable too, not
just recall. Full breakdown, per-PR results, and methodology:
benchmark/core_v3/README.md.
| metric | value | context |
|---|---|---|
| PRs reviewed | 30 (14 defective, 16 control) | one target repo |
| F1 | 0.500 | against seeded defects only |
| Precision | 0.353 | 1.00 false positive per control PR |
| Recall | 0.857 | 12 of 14 defects found |
| Avg cost / PR | $0.0045 | low and high model together |
| Avg time / PR | 28.9s | sequential, no concurrency |
From a checkout:
npm install
npm test # unit, script and benchmark tests
npm run check # tsc --noEmit
npm run docs:build # rebuild docs/ from docs/md/
npm run e2e # end-to-end CLI loop
npm run review-local-e2e # fake-AI local review loop
npm run dashboard:smoke # browser smoke test