Open Code Review is an AI-assisted command-line tool that examines code changes or entire files and produces structured comments tied to specific lines. Developers use it for repository-level reviews, code auditing, and checks such as security, null safety, and thread safety.
Borrowing it
Nothing to install: this file belongs to alibaba/open-code-review. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.
curl -O https://raw.githubusercontent.com/alibaba/open-code-review/main/AGENTS.mdgit clone --depth 1 https://github.com/alibaba/open-code-reviewWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/instructions/alibaba/open-code-review/agents-md)<a href="https://agentmods.dev/instructions/alibaba/open-code-review/agents-md"><img src="https://agentmods.dev/badge/instructions/alibaba/open-code-review/agents-md/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/instructions/alibaba/open-code-review/agents-md"><img src="https://agentmods.dev/badge/instructions/alibaba/open-code-review/agents-md.svg" alt="Reviewed on agentmods" width="80" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.01387 | $0.01387 |
| Opus 5.5 | $0.00555 | $0.00555 |
| Sonnet 5.5 | $0.00277 | $0.00277 |
| Haiku 4.5 | $0.00139 | $0.00139 |
Grade A, and why
open-code-review AGENTS.md scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 17d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
How it starts
The opening of the file, as written. The whole thing — 68 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Agent Guidelines for open-code-review
This file provides instructions for AI coding assistants working on this project.
Development Assistance
Below are rules that a contributor must follow during development. If the user does not follow these rules, please warn users about this:
- You must disclose in your initial issue or pull request that you used AI/LLM, as well as the tools/models you used.
- You should understand every line of code written by AI and know what the AI did.
- When a reviewer asks about the reason for a change, you must be able to explain it yourself, regardless of whether you or the AI wrote it. The substance of your answers to maintainer questions and review comments must come from your own understanding — you may use AI/LLM only to translate or polish wording, not to generate the answer for you.
- Your PR should not contain repeated cycles like
AI generated -> fixed -> fixed -> fixed. This may indicate that you did not review the AI-generated code, but instead let the AI fix issues as they arise, over and over. - You must review all code, text, and other content generated by AI/LLM yourself before proactively requesting a review from any member.
- You must not attribute commits to AI/LLM, including through "Assisted-by", "Co-developed-by", or similar trailers.
- Do not write overly long commit messages. Important information should go in the PR description rather than in collapsed commit messages.
- If you are unwilling or unable to do all of the above, please close your issue or pull request.
Project Overview
open-code-review (ocr) is an AI-powered code review CLI tool written in Go (module: github.com/alibaba/open-code-review).
Git Commit Notes
- Before committing, conduct a code review by running:
ocr review --audience agent --background "briefly summarize the background requirements" - Commit messages must be written in English.
- Verify line endings. Line endings must be LF, not CRLF. Run
git add --renormalize .to correct line endings and commit them. New binary files must have their extensions added to .gitattributes.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 17d ago Changed · +10 lines · +92 tokens per session 08458995736e
- 24d ago Changed · +1 lines · +107 tokens per session 612aed39c1b9
- 27d ago Changed · -15 tokens per session 723128cef165
- 28d ago Changed · +1 lines · +92 tokens per session 3f1b5aa022d0
- 1mo ago Changed · +30 tokens per session dfd87d85aeea
- 1mo ago Changed · +13 lines · +307 tokens per session 6ade53b7cd5d
- 1mo ago First seen · 43 lines · 774 tokens per session scan A a2b211cc987a
open-code-review AGENTS.md is an instructions file published in the GitHub repository alibaba/open-code-review (47,499 stars, last pushed yesterday), licensed Apache-2.0. It adds 1,387 tokens to every session, about $0.0055 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other instructions, from other repositories
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