/code-review

Provide a code review for the given pull request.

To do this, follow these steps precisely:

1. Use an agent to check if the pull request (a) is closed, (b) is a draft, (c) does not need a code review (eg. because it is an automated pull request, or is very simple and obviously ok), or (d) already has a code review from you from earlier. If so, do not proceed.
2. Use another agent to give you a list of file paths to (but not the contents of) any relevant CLAUDE.md files from the codebase: the root CLAUDE.md file (if one exists), as well as any CLAUDE.md files in the directories whose files the pull request modified
3. Use an agent to view the pull request, and ask the agent to return a summary of the change
4. Then, launch 4 parallel agents to independently code review the change. The agents should do the following, then return a list of issues and the reason each issue was flagged (eg. CLAUDE.md adherence, bug, historical git context, etc.): a. Agents #1 and #2: Independently audit the changes to make sure they compily with the CLAUDE.md b. Agent #3: Read the file changes in the pull request, then do a shallow scan for obvious bugs. Avoid reading extra context beyond the changes, focusing just on the changes themselves. Focus on large bugs, and avoid small issues and nitpicks. Ignore likely false positives. c. Agent #5: Read the git blame and history of the code modified, to identify any bugs in light of that historical context
5. For each issue found in #4, launch a parallel agent that takes the PR, issue description, and list of CLAUDE.md files (from step 2), and returns a score to indicate the agent's level of confidence for whether the issue is real or false positive. To do that, the agent should score each issue on a scale from 0-100, indicating its level of confidence. For issues that were flagged due to CLAUDE.md instructions, the agent should double check that the CLAUDE.md actually calls out that issue specifically. The scale is (give this rubric to the agent verbatim): a. 0: Not confident at all. This is a false positive that doesn't stand up to light scrutiny, or is a pre-existing issue. b. 25: Somewhat confident. This might be a real issue, but may also be a false positive. The agent wasn't able to verify that it's a real issue. If the issue is stylistic, it is one that was not explicitly called out in the relevant CLAUDE.md. c. 50: Moderately confident. The agent was able to verify this is a real issue, but it might be a nitpick or not happen very often in practice. Relative to the rest of the PR, it's not very important. d. 75: Highly confident. The agent double checked the issue, and verified that it is very likely it is a real issue that will be hit in practice. The existing approach in the PR is insufficient. The issue is very important and will directly impact the code's functionality, or it is an issue that is directly mentioned in the relevant CLAUDE.md. e. 100: Absolutely certain. The agent double checked the issue, and confirmed that it is definitely a real issue, that will happen frequently in practice. The evidence directly confirms this.
6. Filter out any issues with a score less than 80. If there are no issues that meet this criteria, do not proceed.
7. Finally, comment back on the pull request with a list of issues you found. When writing your comment, keep in mind to: a. Keep your output brief b. Avoid emojis c. Link and cite relevant code, files, and URLs

Examples of false positives, for steps 4 and 5:

• Pre-existing issues
• Something that looks like a bug but is not actually a bug
• Pedantic nitpicks that a senior engineer wouldn't call out
• Issues that a linter, typechecker, or test runner will catch (eg. failing tests, lint errors, type errors). Do not run these to verify; assume that they will be run as part of CI.
• General code quality issues (eg. lack of test coverage, general security issues), unless explicitly required in CLAUDE.md
• Issues that are called out in CLAUDE.md, but explicitly silenced in the code (eg. due to a lint ignore comment)

Notes:

• Use gh to interact with Github (eg. to fetch a pull request, or to create inline comments), rather than web fetch
• Make a todo list first
• You must cite and link each bug (eg. if referring to a CLAUDE.md, you must link it)
• For your comment, follow the following format precisely (assuming for this example that you found 3 issues):

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Code review

Found 3 issues:

1. (CLAUDE.md says "<...>")

2. (some/other/CLAUDE.md says "<...>")

3. (bug due to )

🤖 Generated with Claude Code

_{- If this code review was useful, please react with 👍. Otherwise, react with 👎.}

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• Or, if you found no issues:

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Auto code review

No issues found. Checked for bugs and CLAUDE.md compliance.

🤖 Generated with Claude Code

• When linking to code, follow the following format precisely, otherwise the Markdown preview won't render correctly: https://github.com/anthropics/claude-cli-internal/blob/c21d3c10bc8e898b7ac1a2d745bdc9bc4e423afe/package.json#L10-L15
  • Requires full git sha
  • Repo name must match the repo you're code reviewing

  • sign after the file name

  • Line range format is L[start]-L[end]
  • Provide at least 1 line of context before and after, centered on the line you are commenting about (eg. if you are commenting about lines 5-6, you should link to L4-7)