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locus review

AI-powered code review on pull requests. Reviews agent-managed PRs or specific PRs with optional focus areas.

Run AI-powered code reviews on GitHub pull requests. By default, reviews all open PRs with the agent:managed label. Can also target a specific PR by number.

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Usage

locus review [pr-number] [options]

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Options

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Description

--focus <areas>

Comma-separated review focus areas (e.g., "security,performance,testing")

--dry-run

Generate the review without posting it as a PR comment

--model <name>

Override the AI model for this review

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Modes

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Review All Agent PRs

When called without arguments, finds all open PRs labeled agent:managed and reviews each one.

locus review

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Review a Specific PR

Pass a PR number to review a single pull request.

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Focused Review

Use --focus to direct the AI's attention to specific areas.

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What the Review Covers

The AI reviewer checks the PR diff for:

  • Correctness -- bugs, logic errors, edge cases

  • Security -- injection, XSS, auth issues, secret exposure

  • Performance -- N+1 queries, unnecessary allocations, missing caching

  • Maintainability -- naming, complexity, code organization

  • Testing -- missing tests, inadequate coverage

Each finding includes the file location, description of the issue, why it matters, and how to fix it. The review ends with an overall assessment: APPROVE, REQUEST_CHANGES, or COMMENT.

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Review Output

Unless --dry-run is specified, the review is posted as a comment on the PR with the heading "Locus AI Review". The comment includes the provider and model used.

In dry-run mode, the review is generated and streamed to the terminal but not posted.

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Project Context

The reviewer has access to your project context via LOCUS.md, so it understands your tech stack, conventions, and constraints when evaluating changes.

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Examples

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