Guide · Agent skill
How to use the Open Code Review Delegate agent skill
Updated · written with AI from the project's own documentation and checked against our catalogue data
The open-code-review-delegate skill teaches an AI agent to review code changes in a git repository in a fixed, checkable order. The ocr command-line tool picks which changed files matter and which review rules apply, while the agent reads the diffs and writes the comments itself. After this guide you will be able to install the skill, ask your agent for a review in plain language, and read a report that accounts for every changed file.
Quick start
- 1Install the ocr CLI. Install @alibaba-group/open-code-review with npm or download a GitHub release binary, and confirm git is available.
- 2Download the skill ZIP. Get the open-code-review-delegate ZIP from this page.
- 3Unzip into a skills folder. Extract it into ~/.claude/skills/ for all projects or into a project's .claude/skills/ folder.
- 4Open your repository. Change into the git repository you want reviewed.
- 5Ask for a review. Request a review in plain words, such as reviewing your branch against main or a single commit.
- 6Check coverage. Confirm every changed file is listed as reviewed or skipped with a reason.
- 7Act on findings. Read the severity-grouped findings and decide what to fix; ask for fixes only if you want them applied.
What the skill makes the agent do
Normally, a code review tool such as open-code-review calls a separate LLM service to do the reasoning. This skill switches that around. The OCR CLI handles deterministic work: deciding which changed files are reviewable and which review rules apply to each file. The host agent, the AI assistant you are already using, reads the diffs and writes the review comments with its own model.
The agent works through a fixed sequence: preview the changes, fetch rules, read each diff, review each file, format comments, and report. It then checks coverage, so every file is listed as either reviewed or skipped with a reason, and findings are grouped by severity (critical and high, medium, low).
Install the skill
Download the skill ZIP from this page and unzip it into one of two locations. For a personal install available in all your projects, use ~/.claude/skills/. For a single project, use the .claude/skills/ folder inside that project.
If you use the Claude apps instead, upload the ZIP under Settings → Capabilities → Skills.
The skill needs the ocr CLI on your machine. The source describes two ways to get it: install it with npm, or download a binary from the GitHub release. The npm package name is @alibaba-group/open-code-review.
- Personal install: unzip into ~/.claude/skills/
- Project install: unzip into the project's .claude/skills/ folder
- Claude apps: Settings → Capabilities → Skills, then upload the ZIP
npm install -g @alibaba-group/open-code-reviewRequirements before you start
You need three things: the ocr CLI installed, git available in the repository you want reviewed, and a host AI agent that can read files and run shell commands. The skill does not need a configured LLM endpoint, because the review is done by your agent rather than by OCR.
- ocr CLI installed via npm (@alibaba-group/open-code-review) or a GitHub release binary
- git available in the repository
- A host AI agent capable of reading files and running shell commands
Trigger the review with natural requests
You do not need to type commands yourself. Ask the agent in plain language, for example to review your current branch against main, or to review one commit. The agent chooses the matching ocr delegate preview options. The source's common invocations map to these scenarios: uncommitted workspace changes, a branch comparison, and a single commit.
If you have requirement context, such as a ticket description, you can include it. The source says --background passes business context into the preview output for reference during review, and --background-file reads it from a Markdown file.
- Review my uncommitted changes before I commit.
- Review the feature branch against main and flag anything risky.
- Review commit abc123 and list every file as reviewed or skipped.
- Review this branch and fix only the critical and high issues.
ocr delegate preview --from main --to featureRead the report
Each finding is a comment with a path, the review text, optional line numbers in the new file, and optional category and severity. The summary includes total_files, reviewed_files, skipped_files, and coverage_rate. Any skipped file must come with a reason.
Findings are grouped by severity. Critical and high items are always reported. Medium items are reported with context. Low items appear only when they are clearly valuable. The source says likely false positives are discarded silently.
- Critical/High: bugs, security issues, data loss risks
- Medium: performance, error handling gaps, maintainability
- Low: style nits and minor suggestions, only if clearly valuable
Safety notes: scripts and network
The skill runs scripts, because it calls the ocr CLI and git. The source lists the skill as using no network of its own. Diffs are read by the host agent and sent to that agent's model, so check that your agent's model provider is approved to see the source code you are reviewing. If the repository is sensitive, do not use this mode.
The diff commands disable external diff programs, text conversion, and color, so the output is plain patches. The skill also tells the agent to write large diffs to a file outside the repository and delete that file after reading it.
- Runs scripts: yes (ocr and git commands)
- Uses network: no, according to the source
- Diffs are sent to the host agent's model provider
Tips for better reviews
Run the review inside the repository you want checked, because ocr delegate uses the current directory. Use --repo /path to point elsewhere. Keep large changes manageable: the agent reviews them in batches grouped by shared rules.
Remember the limit of this skill. It reads diffs and can optionally apply fixes, but it does not run your tests to confirm correctness.
- Run from the repo root, or pass --repo /path
- Pass --exclude with comma-separated patterns to skip files
- Use --background-file for long requirement documents; the source sets a 1 MiB raw file limit and an 8000-character sanitized limit
What people use it for
- Reviewing a feature branch against main before opening a merge request
- Checking uncommitted workspace changes before a commit
- Reviewing a single commit and getting a per-file coverage list
- Using your existing AI agent's model for review instead of a separately configured LLM endpoint
Frequently asked questions
Is the open-code-review-delegate skill free?
The skill is licensed under Apache-2.0, as stated in its source. The source does not list prices, so check the repository for any cost details before relying on it.
What do I need to run this skill?
You need the ocr CLI installed through npm (@alibaba-group/open-code-review) or a GitHub release binary, git in the repository, and a host AI agent that can read files and run shell commands. You do not need an LLM endpoint configured for OCR.
Where do I install an agent skill like this?
Unzip the downloaded ZIP into ~/.claude/skills/ for personal use or into a project's .claude/skills/ folder. In the Claude apps, upload the ZIP under Settings → Capabilities → Skills.
Does the skill run tests to check my code?
No. The source says it only reads diffs and optionally applies fixes. It does not verify correctness by running tests.
Does this skill send my code over the network?
The source says the skill uses no network itself. However, the diffs are read by your host agent and sent to that agent's model, so you should confirm that provider is approved for your code.
How is this different from running open-code-review normally?
In delegation mode, OCR does not call a separate LLM service. OCR only selects files and rules, and your host agent does the actual review. The source frames this as the difference between OCR calling an endpoint and the agent reviewing with its own model.
New agent skills, repos and AI tools — every week
The best new skills and open-source projects, the fastest-growing repos, and one free prompt. Five minutes to read. Unsubscribe anytime.
Our verdict
This skill suits developers and teams who already use an AI agent and want a repeatable review that accounts for every changed file, driven by that agent's own model. It is a poor fit if you need a fully automated pipeline without an agent, if your code cannot be shared with the agent's model provider, or if you expect the review to confirm correctness by running tests.
Download the skill