Open Code Review

This Codex plugin skill intentionally mirrors the canonical skill at skills/open-code-review/SKILL.md. Keep both files synchronized when updating OCR agent instructions; a symlink is avoided because plugin installs may only materialize the plugin subtree.

A skill for invoking open-code-review (ocr) — an open-source AI code review CLI that reads Git diffs and generates structured, line-level review comments.

Workflow

Step 1: Gather Business Context

Analyze the review target (commits, branch, or changes) to extract concise business context. Pass this context via --background to improve review quality.

Step 2: Run Code Review

Do not pre-check whether ocr is installed — skip probes like command -v ocr or ocr --version. Assume the CLI is available and run the review directly; that saves a tool call on the common path. Only if the review fails with command not found should you install it per Troubleshooting.

Run the OCR command with appropriate flags. Always pass business context via --background when available:

ocr review --audience agent --background "business context here" [user-args]

Argument handling:

• Background context (RECOMMENDED): use --background "context" or -b "context" to provide business context for better review quality
• Default (no user arguments): reviews staged, unstaged, and untracked changes (workspace mode)
• Specific commit: use --commit or -c to review a single commit against its parent
• Branch comparison: use --from <ref> and --to <ref> to review diff between two refs
• Timeout: effective timeout per review group = --timeout × review rounds. Default --timeout 15 with default effort medium (2 rounds) gives 30 minutes; low/high give 15/45 minutes.
• Concurrency: default concurrency is 8 file workers; reduce with --concurrency <n> if rate limits are hit
• Preview mode: use --preview or -p to preview which files will be reviewed without running the LLM
• Output file: use --output <path> to write the full result to a file instead of stdout. If the command fails with unknown flag: --output, do not continue the review with plain stdout. Ask the user whether to upgrade (npm i -g @alibaba-group/open-code-review@latest) and wait for the answer before proceeding. After the user confirms and the upgrade succeeds, rerun with --output.
• Installation: if ocr command is not found, install it by running npm i -g @alibaba-group/open-code-review

Common invocation patterns:

Output mode:

• Always use --audience agent to suppress progress UI and emit only the final summary
• Prevent output truncation: For large reviews or restricted tool environments, pass --output /tmp/ocr_out.txt and inspect the file in full via a file reading tool instead of piping stdout through tail or head, which drops earlier review comments.

On failure: If ocr review exits non-zero (e.g. an LLM connection error), do not retry blindly — consult the Troubleshooting section below for the matching fix before re-running.

Step 3: Report

OCR output includes structured severity (critical / high / medium / low) and category (bug / security / performance / maintainability / test / style / documentation / other) on each comment. Present results grouped by severity, discarding low severity items that are likely false positives or nitpicks.

Step 4: Fix

Before applying fixes, check whether the user requested automatic fixes:

• If the user explicitly requested "review and fix" or similar, proceed with automatic fixes
• If the user only requested "review" without fix intent, ask for permission before applying any changes

When fixing issues and suggestions:

• Focus on critical, high, and medium severity items
• Apply fixes directly to the code when safe and well-defined
• For complex fixes requiring manual intervention, clearly describe what needs to be done

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