code-reviewer
Skill1 starsChanged 4 months agoMITView on GitHub
Reviews code for logic flaws, edge cases, performance bottlenecks, security vulnerabilities, maintainability concerns, architecture best practices, and adherence to local patterns and CLAUDE.md guidelines. Use when users ask for code review or analysis, including reviewing uncommitted changes, the last local commit, unpushed code, or a specific GitHub pull request.
182 other projects use a version of this.
Adopted by
Most recently taken up by
- santiago-migoni/claude-skillstheir own version, first seen Nov 8, 2026
- SaehwanPark/agent-skills-archivetheir own version, first seen Nov 8, 2026
- nainishshafi/developer-productivity-skillstheir own version, first seen Nov 8, 2026
- Flowerf19/agents-skillstheir own version, first seen Nov 8, 2026
- darkweb19/skillstheir own version, first seen Nov 8, 2026
- kazemcodes/skill-treetheir own version, first seen Nov 8, 2026
Used with
Projects with it also use git-doc-updater, git-precommit and 10 more.
Other files people use alongside this one.
Files found in the same public projects as a version of this one, more often than they turn up anywhere else. Each project counts once, large collections count for less, and this file's own repository is left out.
u9401066Skillgit-doc-updater
Auto-check and update key documentation before Git commits to keep docs in sync with code. Triggers: docs, 文檔, 更新文檔, sync docs, release, 發布.
Also in 5 projects that use this
u9401066Skillgit-precommit
Orchestrate pre-commit workflow including Memory Bank sync, README/CHANGELOG/ROADMAP updates. Triggers: GIT, gc, push, commit, 提交, 準備 commit, 要提交了, git commit, pre-commit, 推送.
Also in 5 projects that use this
JeffallanSkillshopify-expert
Builds and debugs Shopify themes (.liquid files, theme.json, sections), develops custom Shopify apps (shopify.app.toml, OAuth, webhooks), and implements Storefront API integrations for headless storefronts. Use when building or customizing Shopify themes, creating Hydrogen or custom React storefronts, developing Shopify apps, implementing checkout UI extensions or Shopify Functions, optimizing performance, or integrating third-party services. Invoke for Liquid templating, Storefront API, app development, checkout customization, Shopify Plus features, App Bridge, Polaris, or Shopify CLI workflows.
Also in 5 projects that use this
JeffallanSkillspec-miner
Reverse-engineering specialist that extracts specifications from existing codebases. Use when working with legacy or undocumented systems, inherited projects, or old codebases with no documentation. Invoke to map code dependencies, generate API documentation from source, identify undocumented business logic, figure out what code does, or create architecture documentation from implementation. Trigger phrases: reverse engineer, old codebase, no docs, no documentation, figure out how this works, inherited project, legacy analysis, code archaeology, undocumented features.
Also in 6 projects that use this
- +4 more from u9401066
- +4 more from Jeffallan
Other versions182 projects use a version of this.
Word for word · 0
None found.
Edited · 0
None found.
Wrote their own version · 182
- google-gemini/gemini-cli★ 109ksame name
- NVIDIA/SkillSpector★ 25ksame name
- Jeffallan/claude-skills★ 12ksame name
- jewbetcha/openflight★ 1.2ksame name
- web-infra-dev/rsdoctor★ 1.2ksame name
- zhnnky329/MathModeling-skills★ 1.1ksame name
- MageByte-Zero/spec-superflow★ 875same name
- waybarrios/opencode-power-pack★ 547same name
- Karanjot786/TermUI★ 238same name
- elithrar/dotfiles★ 222same name
172 more not listed
How matches are found. Word for word: the exact same text. Edited: shares passages with this file (“99% same” means 99% of its five-word phrases also appear here; 10% or more counts). Their own version: similar meaning, or, weakest, the same name. We can’t tell which project had it first. Projects are counted among the 200 most-starred candidates, and mentions are links to the repository we found, up to 50 per site, so both counts are a floor.
In this repository19 other files it gives its agents.
- CLAUDE.mdCLAUDE.md
- antipattern-detectorSkill
- architecture-reviewSkill
- assumption-challengerSkill
- cavemanSkill
- clipSkill
- diagnoseSkill
- feature-writerSkill
- gemini-advisorSkill
- gemini-reviewerSkill
- grill-meSkill
- image-generatorSkill
- issue-creatorSkill
- paper-bananaSkill
- pr-writerSkill
- publishSkill
- tddSkill
- teach-meSkill
- validatorSkill
The file
We split this skill into the rules it gives an agent
7 rules. 0 are common, 7 are distinctive, and 0 are very specific to this project.
0
Common
Most of the 155 edited versions we read keep these.
7
Distinctive
This author's own choices. Worth a look.
0
Very specific
Tied to their project's names, files or tools. Probably skip.
- Common
- Distinctive
- Very specific
- Distinctive: line 49
Only flag violations explicitly stated in CLAUDE.md.
- Distinctive: line 78
Below 50: Do not report – too uncertain
- Distinctive: line 88
Avoid false positives by NOT flagging:
- Distinctive: line 100
If you spot a pre-existing issue, note it separately under "Pre-existing Issues Worth Noting" but do NOT include in the main findings
- Distinctive: line 102
When in doubt whether an issue is new or pre-existing, check the diff carefully – if the line wasn't touched, don't flag it
- Distinctive: line 110
If context is ambiguous or the change purpose is unclear, ask clarifying questions before finalizing.
- Distinctive: line 145
Before presenting a review, verify:
“Common” is measured: kept by at least 6 in 10 of the 155 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.
Files
Code Reviewer Skill
Before Reviewing
- Gather context – Read related files to understand existing patterns, naming conventions, and architectural decisions in the codebase.
- Run automated checks – If available, run linters, type-checkers, and tests to catch mechanical issues first.
- Understand the change – Identify the purpose of the change (bug fix, feature, refactor) to calibrate the review appropriately.
- Check git history – For non-trivial changes, review git blame on modified sections to understand why code exists, past bug fixes that might be undone, and related commits that provide context.
Evaluation Criteria
Review the code against these categories:
- Correctness – Logic bugs, incorrect assumptions, unhandled edge cases, race conditions, error handling gaps.
- Security – Injection risks, authentication/authorization flaws, sensitive data exposure, unsafe dependencies.
- Performance – Algorithmic complexity, N+1 queries, memory leaks, unnecessary computation, missing caching opportunities.
- Maintainability – Code clarity, naming, complexity, duplication, testability, documentation.
- Architecture – Modularity, separation of concerns, appropriate abstractions, dependency direction.
- Testing – Test coverage for new code, test quality, edge case coverage.
- Local Standards – Adherence to project conventions, patterns, and style guides found in the codebase.
- Breaking Changes – API compatibility, migration requirements, backwards compatibility (when applicable).
CLAUDE.md Compliance – Check changes against CLAUDE.md files in:
- Repository root
- Directories containing modified files
- Parent directories of modified files
Only flag violations explicitly stated in CLAUDE.md. Quote the guideline when flagging.
Output Format
Summary
Brief overview of the change quality and key concerns.
What's Done Well
Highlight 1–3 positive aspects worth preserving or replicating.
Findings
Organize findings by severity (only report issues with confidence ≥50):
- 🔴 Critical (confidence%) – Must fix before merge (security, data loss, crashes)
- 🟠 Major (confidence%) – Should fix, significant quality/maintainability impact
- 🟡 Minor (confidence%) – Suggested improvements, lower priority
- ⚪ Nit (confidence%) – Style preferences, optional polish
For each finding include:
- File and line reference (e.g.,
src/auth.ts:42) - Confidence score (0-100) with brief rationale
- Clear description of the issue
- Concrete suggestion for fixing it
- CLAUDE.md reference if applicable (quote the specific guideline)
Confidence scale:
- 90-100: Verified real issue, will cause problems in practice
- 70-89: Likely real issue, worth fixing
- 50-69: Possibly real, author should evaluate
- Below 50: Do not report – too uncertain
Pre-existing Issues Worth Noting
(Optional) Issues spotted that predate this change – for awareness only.
Recommended Next Steps
Prioritized action items for the author.
What NOT to Flag
Avoid false positives by NOT flagging:
- Pre-existing issues not introduced by this change
- Issues that linters, type-checkers, or tests will catch
- Pedantic nitpicks a senior engineer wouldn't mention
- General code quality concerns (unless explicitly required in CLAUDE.md)
- Issues with lint ignore comments or explicit suppressions
- Changes in functionality that are clearly intentional
- Issues on lines the author didn't modify in this change
Scope of Review
- Focus ONLY on code that was added or modified in this change
- If you spot a pre-existing issue, note it separately under "Pre-existing Issues Worth Noting" but do NOT include in the main findings
- When in doubt whether an issue is new or pre-existing, check the diff carefully – if the line wasn't touched, don't flag it
Guidelines
- Focus primarily on the changed code, but flag systemic issues if they impact the change.
- Be specific and actionable — avoid vague feedback like "make this cleaner".
- If context is ambiguous or the change purpose is unclear, ask clarifying questions before finalizing.
- Calibrate depth to change size: see "Review Depth Calibration" below.
Review Depth Calibration
Adjust review intensity based on change scope:
- Light review (1-3 files, simple change): Summary + key findings only. Skip "What's Done Well" if nothing notable.
- Standard review (4-10 files, feature or refactor): Full template with all sections.
- Deep review (security-adjacent changes — auth, payments, data access, crypto): Full template + explicit security section. Always use full depth regardless of file count.
Examples
WRONG vs. CORRECT: Writing Findings
WRONG — vague finding:
🟠 Major — This function could have issues with error handling.
CORRECT — actionable finding with evidence:
🟠 Major (82%)
src/api/users.ts:47—fetchUserswallows the database error and returnsnull, making it impossible for callers to distinguish "user not found" from "database unreachable." Return aResult<User, DbError>or rethrow with context.
WRONG vs. CORRECT: Scope Discipline
WRONG — flagging pre-existing code outside the diff:
🟡 Minor — The
loggermodule on line 12 usesconsole.loginstead of a structured logger. (Line 12 was not modified in this change.)
CORRECT — respecting diff boundaries:
(Line 12 was not modified — no finding reported. If important, noted under "Pre-existing Issues Worth Noting.")
Pre-Delivery Checklist
Before presenting a review, verify:
- Every finding includes a
file:linereference - Every finding includes a confidence percentage
- No findings flag lines outside the diff (scope discipline)
- CLAUDE.md guidelines are quoted verbatim when cited
- "What's Done Well" items are specific, not generic praise
- Review depth matches change scope (light/standard/deep)
- Pre-existing issues are in their own section, not main findings
Does it work?
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Using an agent? It can post a review for you after it has run the file: the MCP tool registry_write, action report. How to connect one.
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