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Code Review Expert for Claude

Comprehensive code review rules for thorough analysis and constructive feedback

by JSONbored·added 2025-09-16·
HarnessClaude Code
Review first review before installing

Open the source and read safety notes before installing.

Citation facts

Source-backed facts for citing this resource, derived directly from the registry — also available as plain text for AI assistants.

Source URLs
https://google.github.io/eng-practices/review/reviewer/looking-for.html, https://github.com/JSONbored/awesome-claude/blob/main/content/rules/code-review-expert.mdx
Privacy notes
Code review reads source diffs that may contain secrets or proprietary code; keep credentials and sensitive snippets out of review comments and shared logs.
Author
JSONbored
Claim status
unclaimed
Last verified
2025-09-16

Decision playbook

Review trust signals before you adopt

Signals are present but mixed. Use the checklist below to confirm the source and operational safety for your environment.

Required checks are still incomplete. Finish source and safety verification before adopting this resource.

Compare context
Selected

0

Current score

68

Baseline

Delta

No baseline selected

No major trust-signal divergence detected in the current selection.

Source and provenance checks

Complete

Confirm ownership and provenance before trusting install instructions.

  • Source link availableRequired

    Open the canonical repository and verify ownership.

    Done
  • Source provenance statusRequired

    Marked as source-backed.

    Done
  • Metadata reviewed

    Registry metadata indicates a reviewed listing.

    Done

Safety and privacy checks

Required checks missing

Validate risk disclosures before installation or API wiring.

  • Safety notes presentRequired

    No safety notes listed.

    Pending
  • Privacy notes presentRequired

    Review data handling notes before connecting accounts or secrets.

    Done
  • Trust level risk gateRequired

    Trust level does not block evaluation.

    Done

Package and install checks

Needs review

Check package metadata and artifact integrity signals.

  • Install payload available

    Install or copy payload is available for review.

    Done
  • Package verification flag

    No package verification flag provided.

    Pending
  • Checksum metadata

    No checksum provided for downloaded artifact.

    Pending

Compare-driven decision checks

Needs review

Use compare context to validate trade-offs before adoption.

  • Compare tray has multiple entries

    Add at least one more entry to compare trust differences.

    Pending
  • Baseline comparison available

    No baseline peer selected yet.

    Pending
  • Diverging trust signals identified

    No major trust-signal divergence found.

    Pending

Setup at a glance

Copy & paste

Copy-ready — paste the snippet to get started.

Install command

Not provided

Config snippet

Not provided

Copy snippet

Provided

Prerequisites

None

Platforms

1 listed

Difficulty

3/100

Adoption plan

Balanced adoption plan

Current risk score 30/100. Use staged verification before broader rollout.

Risk 30
Adoption blockers
  • Safety notes are missing.

Pre-adoption checks

Validate source and review signals before any execution.

  • Confirm source provenanceRequired

    Source URL/provenance metadata is present.

    Done
  • Confirm metadata review state

    Listing has review metadata.

    Done
  • Verify install payload

    Install/config payload exists and can be inspected.

    Done

Security checks

Confirm safety, privacy, and package integrity signals.

  • Review safety notesRequired

    Safety notes missing; review source code paths before execution.

    Pending
  • Review privacy notesRequired

    Privacy notes are present.

    Done
  • Verify package integrity metadata

    No package verification/checksum metadata.

    Pending

Rollout

Adopt in controlled steps based on the selected plan.

  • Run in isolated sandbox firstRequired

    Use a constrained sandbox and observe behavior across multiple tasks.

    Pending
  • Roll out graduallyRequired

    Roll out to a small cohort before wider usage.

    Pending
  • Set monitoring and fallback

    Define rollback path and monitor errors after adoption.

    Pending

Evidence readiness

Evidence readiness matrix · balanced

Missing required evidence: Safety notes. Risk score 31.

Risk 31

Source provenance

Present

Source repository/provenance is listed.

Required in this preset

Metadata review

Present

Review metadata is present.

Required in this preset

Safety notes

Missing

Safety notes are missing.

Required in this preset

Privacy notes

Present

Privacy notes are present.

Optional in this preset

Package integrity

Missing

Package integrity metadata is missing.

Optional in this preset

Install payload

Present

Install payload is available.

Required in this preset

Required gaps: Safety notes

Decision timeline

Decision timeline · balanced

Blocking gaps: Review safety notes. Risk 28.

Risk 28

triage

Confirm source provenanceRequired

Source/provenance metadata is available.

Done

triage

Check metadata review statusRequired

Review metadata is available.

Done

verify

Review safety notesRequired

Safety notes are missing.

Pending

verify

Review privacy notes

Privacy notes are available.

Done

verify

Validate package integrity metadata

Package integrity metadata is missing.

Pending

rollout

Verify install payload and commandsRequired

Install payload is available.

Done

Blockers: Review safety notes

Safety & privacy surface

Safety & privacy surface

1 privacy note across 1 risk area. Review closely: credentials & tokens.

1 area
  • PrivacyCredentials & tokensCode review reads source diffs that may contain secrets or proprietary code; keep credentials and sensitive snippets out of review comments and shared logs.

Privacy notes

  • Code review reads source diffs that may contain secrets or proprietary code; keep credentials and sensitive snippets out of review comments and shared logs.

Schema details

Install type
copy
Reading time
1 min
Difficulty score
3
Troubleshooting
Yes
Breaking changes
No
Skill and platform metadata
Retrieval sources
https://google.github.io/eng-practices/review/reviewer/looking-for.htmlhttps://google.github.io/eng-practices/review/reviewer/https://google.github.io/eng-practices/review/reviewer/standard.html
Full copyable content
You are a code review expert focused on providing comprehensive, constructive feedback. Your approach includes:

## Review Priorities

### 1. Security & Safety
- Identify potential security vulnerabilities
- Check for exposed credentials or sensitive data
- Review authentication and authorization logic
- Validate input sanitization and SQL injection prevention

### 2. Code Quality
- Check for adherence to coding standards
- Identify code smells and anti-patterns
- Review naming conventions and clarity
- Ensure proper error handling

### 3. Performance
- Identify performance bottlenecks
- Review algorithm complexity
- Check for memory leaks
- Optimize database queries

### 4. Maintainability
- Ensure code is well-documented
- Check for proper abstraction levels
- Review test coverage
- Validate modularity and reusability

## Review Process

1. **Initial Assessment**: Quick scan for critical issues
2. **Detailed Analysis**: Line-by-line review with context
3. **Constructive Feedback**: Provide specific, actionable suggestions
4. **Educational Moments**: Explain the 'why' behind recommendations

About this resource

You are a code review expert focused on providing comprehensive, constructive feedback. Your approach includes:

Review Priorities

1. Security & Safety

  • Identify potential security vulnerabilities
  • Check for exposed credentials or sensitive data
  • Review authentication and authorization logic
  • Validate input sanitization and SQL injection prevention

2. Code Quality

  • Check for adherence to coding standards
  • Identify code smells and anti-patterns
  • Review naming conventions and clarity
  • Ensure proper error handling

3. Performance

  • Identify performance bottlenecks
  • Review algorithm complexity
  • Check for memory leaks
  • Optimize database queries

4. Maintainability

  • Ensure code is well-documented
  • Check for proper abstraction levels
  • Review test coverage
  • Validate modularity and reusability

Review Process

  1. Initial Assessment: Quick scan for critical issues
  2. Detailed Analysis: Line-by-line review with context
  3. Constructive Feedback: Provide specific, actionable suggestions
  4. Educational Moments: Explain the 'why' behind recommendations

What a Reviewer Checks

The aspects below follow Google's Engineering Practices "What to look for in a code review" guide. Use them as a checklist when reviewing a change.

Aspect What to verify
Design The change belongs in this codebase, and its pieces interact sensibly with the rest of the system.
Functionality The code does what the author intended, and that intent is good for users (including future developers).
Complexity Nothing is more complex than it needs to be at the line, function, or class level; no speculative over-engineering.
Tests Correct, sensible, useful automated tests accompany the change and will actually fail when the code breaks.
Naming Names are long enough to communicate intent, short enough to stay readable.
Comments Comments explain why the code exists, not what it does; they are clear and necessary.
Style & Consistency The code follows the language style guide and matches existing conventions in the codebase.
Documentation Build, test, and behavior changes are reflected in READMEs, references, and other docs.
Every Line Read the human-written code line by line rather than skimming; flag what you do not understand.
Context Evaluate the change against the whole file and system, confirming it improves overall code health.
Good Things Call out genuinely good practices, not just defects, so feedback stays balanced.

Reviewer mindset: approve once the change definitely improves overall code health, even if it is not perfect. Reserve blocking only for issues that would degrade the codebase, and distinguish those from optional Nit: suggestions.

Source citations

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How it compares

Code Review Expert for Claude side by side with 3 alternatives on trust, install, platform support, and disclosed safety notes — all from reviewed registry metadata.

1 trust signal differ across this comparison (Submitter).

Field

Comprehensive code review rules for thorough analysis and constructive feedback

Open dossier

Source-backed rules for deciding when an AI-assisted code review must escalate high-risk changes to security, infrastructure, data, release, or domain owners before merge.

Open dossier

Source-backed rules for reviewing AI-generated request handlers and forms before merge for cross-site request forgery risk, covering state-changing method discipline, anti-CSRF token correctness, SameSite cookie posture, origin and referer checks, and safe handling of cookie-based sessions.

Open dossier

Source-backed rules for reviewing AI-generated database access code for SQL injection before merge, covering parameterized queries, identifier handling, ORM safety, dynamic query construction, least-privilege access, and privacy-safe test evidence.

Open dossier
Next steps
Trust
Review statusReviewedMaintainer reviewedReviewedMaintainer reviewedReviewedMaintainer reviewedReviewedMaintainer reviewed
Package trustPackage not verifiedPackage not verifiedPackage not verifiedPackage not verified
Source provenanceSource-backedSource-backedSource-backedSource-backed
SubmitterDiffersMkDev11jaso0n0818jaso0n0818
Install riskReview firstReview firstReview firstReview first
Notes Safety · Privacy Safety Privacy Safety Privacy Safety Privacy
Brand
Categoryrulesrulesrulesrules
Sourcesource-backedsource-backedsource-backedsource-backed
AuthorJSONboredMkDev11jaso0n0818jaso0n0818
Added2025-09-162026-06-042026-06-222026-06-19
Platforms
Claude Code
Claude Code
Claude Code
Claude Code
Source repo
Safety notes— missingHigh-risk changes can alter auth, authorization, secrets, production data, network exposure, infrastructure, release automation, or dependency trust; escalate before merge instead of relying on a single reviewer. Treat AI-generated patches, summaries, migrations, policy edits, generated clients, and workflow changes as untrusted until the source diff and checks are reviewed. Require a rollback or disablement path for production-facing changes, especially when the blast radius includes customer data, credentials, deployments, billing, or public APIs.A missing CSRF defense lets a malicious page perform state-changing actions as a logged-in user — transferring funds, changing email or password, or deleting data — using the victim's ambient cookies. AI assistants often generate handlers that work in tests yet omit token validation or perform state changes on GET, because the happy path succeeds without any forged cross-site request. Relying on SameSite cookies alone is not sufficient: defaults vary, Lax still allows top-level GET navigations, and some clients or legacy browsers do not enforce it.SQL injection lets an attacker read, modify, or destroy data and sometimes execute commands, so a single concatenated query on user input can compromise the whole database. AI assistants often produce plausible queries that concatenate input or use a raw escape hatch on an otherwise safe ORM, which passes simple tests but is injectable. Running injection-style test inputs against a production database can corrupt or expose real data, so exercise them only in a sandbox with least-privilege credentials.
Privacy notesCode review reads source diffs that may contain secrets or proprietary code; keep credentials and sensitive snippets out of review comments and shared logs.Escalation notes can expose private incident context, customer identifiers, secrets, account IDs, internal topology, or vulnerability details if copied into public PR comments. Use private security channels for embargoed vulnerabilities, secrets, regulated data, and exploit details; keep public PR notes synthetic and minimally revealing. Do not paste raw logs, traces, prompts, database rows, screenshots, or security scan output into review notes unless they have been redacted.CSRF tokens are security credentials; do not paste real tokens, session cookies, or production request captures into public PR comments or issues. Use synthetic accounts and redacted requests when demonstrating a CSRF proof of concept, and avoid attaching real user identifiers. Be careful that anti-CSRF tokens are not written into URLs, analytics, or logs, where they can leak through referer headers or shared dashboards.Database code and its test cases can reference real schemas, credentials, connection strings, and personal data when copied from production examples. Do not paste real connection strings, credentials, or production query results into public PR comments; use synthetic schemas and data. Be careful with error messages that echo SQL or row data, since verbose database errors can leak schema and personal information.
Prerequisites— none listed
  • A pull request, patch, or generated code change with enough diff context to classify the risk.
  • A repository policy that names security, infrastructure, data, API, dependency, and release owners or escalation channels.
  • Access to current CI results, required checks, deployment plan, rollback plan, and affected service ownership.
  • Permission to block approval when the risk class, source evidence, or owner signoff is incomplete.
  • A pull request, diff, or snippet containing an AI-generated or AI-edited request handler, form, or fetch call with enough context to know how the user is authenticated.
  • Knowledge of how the framework manages sessions and CSRF tokens, since built-in protection, cookie defaults, and token helpers differ between frameworks.
  • Awareness of which routes change state and which are read-only, so the review can focus on unsafe methods.
  • Permission to block merge when a cookie-authenticated state change ships without a CSRF defense.
  • A pull request, diff, or snippet containing AI-generated or AI-edited database access code with enough context to know which values come from user input.
  • Knowledge of the database driver, ORM, or query builder in use, since parameterization syntax and safe APIs differ between them.
  • A non-production database or sandbox where injection-style inputs can be exercised without touching real data.
  • Permission to block merge when user input reaches SQL without parameterization or when identifiers are taken from input without an allow-list.
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