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code-review

Reviews code changes using CodeRabbit AI. Use when user asks for code review, PR feedback, code quality checks, security issues, or requests fix-review cycles.

68

Quality

81%

Does it follow best practices?

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SecuritybySnyk

Critical

Do not install without reviewing

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 executable commands, strong validation feedback loops in the install/auth flow, and clean sectioning. The only weakness is minor redundancy in the silence/waiting guidance across two sections.

Suggestions

Consolidate the "stay silent / no intermediate messages" guidance into one place to remove the overlap between the intro paragraph and the Output Handling list.

DimensionReasoningScore

Conciseness

The body is lean and assumes Claude's competence, but the "Stay silent..." paragraph and the Output Handling list reiterate the no-intermediate-messages guidance, a minor redundancy that could be trimmed.

4 / 5

Actionability

Every step ships copy-paste-ready commands (coderabbit --version, install.sh, auth login --agent, review --agent -t committed) plus concrete NDJSON parsing and formatting rules.

5 / 5

Workflow Clarity

The Prerequisites are a numbered sequence with explicit validation checkpoints (re-run --version after install, re-run auth status after login, only continue on success) and clear error-recovery guidance.

5 / 5

Progressive Disclosure

Content is self-contained with well-organized sections (Prerequisites, Review Commands, Output Handling, Result Format, Guardrails) and no nested references; at ~85 lines it is slightly above the simple-skill threshold but stays well-structured.

4 / 5

Total

18

/

20

Passed

Description

73%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 clearly answers what and when with natural trigger terms and a distinct CodeRabbit-specific niche. Its main weakness is a slightly thin "what" clause that understates the summarize-and-fix workflow described in the body.

Suggestions

Expand the "what" clause to name the full workflow, e.g. "Reviews code changes with CodeRabbit AI, summarizes findings by severity, and helps implement follow-up fixes."

Add a couple of natural trigger variants users commonly say, such as "review my PR" or "check my diff".

DimensionReasoningScore

Specificity

"Reviews code changes using CodeRabbit AI" names the domain and one concrete action but does not enumerate the downstream actions (summarize issues, implement fixes) that the body performs, so it is not comprehensive.

3 / 5

Completeness

Both "what" (Reviews code changes using CodeRabbit AI) and "when" (Use when user asks for...) are present and explicit, but the "what" clause is thin and could spell out summarizing and fixing.

4 / 5

Trigger Term Quality

"code review, PR feedback, code quality checks, security issues, fix-review cycles" are natural phrases users would say, with good coverage though a few common variants (e.g. "review my PR") are absent.

4 / 5

Distinctiveness Conflict Risk

Naming the specific tool CodeRabbit AI plus targeted review triggers gives it a clear niche with minimal overlap risk against generic code-quality skills.

5 / 5

Total

16

/

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
openai/plugins
Reviewed

Table of Contents

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