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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.

Quality

85%

Does it follow best practices?

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SecuritybySnyk

Passed

No findings from the security scan

SKILL.md
Quality
Evals
Security

Quality

Content

77%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.

A highly actionable, well-sequenced workflow with executable commands, explicit validation, and strong error-recovery loops. Its weaknesses are systematic repetition of the output-truncation/upgrade guidance across three sections and a monolithic single-file layout where custom rules, advanced flags, and troubleshooting could be split into reference files.

Suggestions

State the output-truncation guidance (`--output <path>` and never piping through tail/head) once and cross-reference it from the other two spots, and merge the duplicated 'unknown flag: --output' upgrade procedure into Troubleshooting only.

Split Custom Review Rules (rule.json format + `ocr rules check`) and Advanced Review Options into reference files (e.g. references/rules.md, references/advanced.md) linked from a short overview section, keeping SKILL.md to the core workflow.

Trim the Gotchas entries that restate body content (e.g. token-limit internals like MAX_TOKENS/MAX_COMPLETION_TOKENS/PLAN_MODE thresholds could move to an advanced reference).

DimensionReasoningScore

Conciseness

The body is operational and free of concept explanations Claude already knows, but guidance is repeated across sections: the `--output` upgrade procedure appears nearly verbatim in both the 'Output file' bullet and the 'unknown flag: --output' troubleshooting entry, and output-truncation advice is stated three times ('Prevent output truncation' bullet, the Output mode section, and the 'Avoid output truncation' gotcha). This matches the 3 anchor ('mostly efficient but includes some unnecessary explanation or could be tightened') — not 4, because the duplication is systematic rather than a couple of trimmable lines, and not 2, since there is no padding or beginner-level explanation.

3 / 5

Actionability

Commands are copy-paste ready and cover the common cases: the base invocation `ocr review --audience agent --background "business context here" [user-args]`, a user-says-to-command table, concrete config commands (`ocr config set llm.url ...`), a complete rule.json example, and a dry-run (`ocr review --preview`). This matches the 5 anchor ('fully executable; copy-paste ready; specific examples cover the common cases'); the 4 anchor would leave minor gaps in the covered cases.

5 / 5

Workflow Clarity

The four-step workflow (Gather Business Context → Run Code Review → Report → Fix) is clearly sequenced, with a dedicated Validation section (exit code 0, comments generated, stderr warnings), a permission checkpoint before applying fixes, and a Troubleshooting section that provides explicit error-recovery loops (e.g. resume with `--resume <id>`, configure LLM then `ocr llm test`). This matches the 5 anchor ('clear sequence with explicit validation steps; feedback loops for error recovery'); the 4 anchor would leave minor validation gaps, which are absent. Note: fix application does include validation and a permission gate, so the destructive-operation cap does not apply.

5 / 5

Progressive Disclosure

The single SKILL.md (~230 lines, no bundle files) is well-sectioned with clear headers, but content that would naturally live in separate reference files is all inline: the full Custom Review Rules guide with a rule.json schema, the Advanced Review Options flag catalog, and the detailed Troubleshooting procedures. This sits at the 3 anchor ('some structure but content that should be separate is inline') — not 4, because the inlined advanced material is substantial rather than a minor organization gap, and not 2, because section headers and the guidance to run `ocr review --help` do provide real structure and navigation.

3 / 5

Total

16

/

20

Passed

Description

85%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.

A strong description: concrete third-person capability list plus an explicit 'Use when' clause with concrete trigger phrases. Keyword coverage is good though missing a few common synonyms (PR, diff, 'code review' as a noun), and the generic review triggers create real overlap risk with built-in code-review skills.

Suggestions

Add a disambiguating phrase so the skill triggers when the user wants an automated/LLM CLI review rather than Claude reviewing the diff itself (e.g. 'Use when the user wants an automated line-level review via the ocr CLI...').

Include the natural noun phrase users say, such as 'code review', 'review my changes', or 'review the diff', alongside the existing verb forms.

Tighten 'With appropriate review rules, can detect various types of issues' to a direct statement of what it detects by default versus with custom rules.

DimensionReasoningScore

Specificity

The description lists multiple concrete actions in third person — 'Performs AI-powered code review on Git changes', 'Produces line-level review comments', 'can automatically apply fixes' — and enumerates detectable issue types (bugs, security vulnerabilities, performance problems). This matches the 5 anchor ('multiple specific concrete actions; comprehensive coverage') and exceeds the 4 anchor, which allows minor coverage gaps; the only soft spot is the hedged 'With appropriate review rules, can detect various types of issues', which is a conditional rather than a gap.

5 / 5

Completeness

It explicitly answers 'what' ('Performs AI-powered code review... Produces line-level review comments and can automatically apply fixes') and 'when' via a concrete 'Use when the user asks to review code, review a pull request, review staged/unstaged changes, review a commit, or compare branches' clause. This matches the 5 anchor exactly (both what and when with concrete trigger phrases); the 4 anchor applies only when the 'when' is less explicit.

5 / 5

Trigger Term Quality

Natural phrases users would say are well covered: 'review code', 'review a pull request', 'review staged/unstaged changes', 'review a commit', 'compare branches', 'code quality issues'. A few common variations are missing ('code review' as a noun phrase, 'PR', 'diff', 'review my changes'), so it sits at the 4 anchor ('good keyword coverage; a few natural terms missing') rather than the 5 anchor's comprehensive synonym/extension coverage.

4 / 5

Distinctiveness Conflict Risk

Naming the `ocr` CLI and alibaba/open-code-review gives it a distinct identity, but the trigger phrases ('review code', 'review a pull request', 'review a commit') are exactly the phrases generic code-review skills trigger on, so it would compete with any general code-review skill in the same library. This lands at the 3 anchor ('somewhat specific but could still overlap with similar skills') — not 4, because the overlap is with the most common skill category rather than a minor edge case, and not 2, because the CLI identity and line-level-comment framing do distinguish it from document or generic review skills.

3 / 5

Total

17

/

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.

Validation — 16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository

alibaba/open-code-review

Path

skills/open-code-review/SKILL.md

Reviewed

Table of Contents

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