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open-code-review

Performs AI-powered code review on Git changes using the `ocr` CLI from alibaba/open-code-review. Use when the user asks to review code, review a pull request, review staged/unstaged changes, review a commit, or compare branches for code quality issues. Produces line-level review comments and can automatically apply fixes when requested. With appropriate review rules, can detect various types of issues including bugs, security vulnerabilities, performance problems, and code quality concerns.

76

Quality

94%

Does it follow best practices?

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SecuritybySnyk

Passed

No findings from the security scan

SKILL.md
Quality
Evals
Security

Quality

Content

88%Weight 40%Scale 1-5

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The body is highly actionable with a clear, validated workflow and concrete executable commands. Its main weaknesses are minor redundancy across sections and a monolithic single-file structure that leaves little room for progressive disclosure into reference files.

Suggestions

Consolidate duplicated guidance: cover output-truncation handling in one place (it currently appears in both the 'Output mode' subsection and the 'Gotchas' section) and state CLI installation once rather than in both Step 2 and Troubleshooting.

State the `--audience agent` directive once in Step 2 and refer back to it instead of repeating the instruction across the argument list, Output mode, and Gotchas.

Move the Custom Review Rules and Troubleshooting sections into separate reference files (e.g. RULES.md, TROUBLESHOOTING.md) so SKILL.md stays a lean overview, improving progressive disclosure for this larger-than-50-line skill.

DimensionReasoningScore

Conciseness

The body is mostly lean CLI-specific guidance that assumes Claude's competence, but a few points are repeated — output-truncation handling appears in both 'Output mode' and 'Gotchas', installation in both Step 2 and Troubleshooting, and `--audience agent` several times — fitting the efficient-with-minor-trims anchor at 4 rather than the lean-every-token-earns-its-place anchor at 5.

4 / 5

Actionability

Provides copy-paste-ready commands (`ocr review --audience agent --background …`, `ocr rules check …`, `ocr config set …`, `npm install -g …`), a user-request-to-command table, an executable JSON rule example, and a concrete output template covering the common cases, matching the fully-executable top anchor.

5 / 5

Workflow Clarity

A clear four-step sequence (gather context → run review → report → fix) is backed by a dedicated Validation section, an on-failure→Troubleshooting feedback loop, and a permission checkpoint before applying fixes, satisfying the explicit-validation-and-feedback-loops anchor; the cap for missing validation on destructive/batch operations does not apply because verification is present.

5 / 5

Progressive Disclosure

The skill is a single well-sectioned file (~200 lines) with clearly signaled one-level external-URL references and no nested references, but no bundle files are used and sections like Custom Review Rules and Troubleshooting are inlined where a leaner overview pointing to separate reference files would fit the top anchor better.

4 / 5

Total

18

/

20

Passed

Description

100%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

The description is exemplary: it states concrete capabilities in third person, provides comprehensive natural-language triggers, and explicitly covers both what the skill does and when to invoke it. No vagueness, fluff, or over-claims are present.

DimensionReasoningScore

Specificity

Lists multiple concrete actions — 'Performs AI-powered code review on Git changes', 'Produces line-level review comments', 'automatically apply fixes', and detecting 'bugs, security vulnerabilities, performance problems' — matching the comprehensive-coverage anchor rather than the minor-gaps anchor at 4.

5 / 5

Completeness

Explicitly answers both what ('Performs AI-powered code review… Produces line-level review comments… apply fixes') and when ('Use when the user asks to review code, review a pull request…') with concrete trigger phrases, matching the top anchor; the 4 anchor's 'when could be more explicit' does not apply.

5 / 5

Trigger Term Quality

Surfaces natural phrases users actually say — 'review code', 'review a pull request', 'review staged/unstaged changes', 'review a commit', 'compare branches' — giving comprehensive coverage of trigger terms rather than the few-missing anchor at 4.

5 / 5

Distinctiveness Conflict Risk

Targets a clear niche (the `ocr` CLI for Git code review) with distinct, specific triggers and minimal overlap with other skills, fitting the clear-niche anchor rather than the minor-overlap anchor at 4.

5 / 5

Total

20

/

20

Passed

Validation

100%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
alibaba/open-code-review
Reviewed

Table of Contents

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