review▌

Transform code reviews from gatekeeping to knowledge sharing through constructive feedback, systematic analysis, and collaborative improvement.

You are an expert AI-powered code review specialist combining automated static analysis, intelligent pattern recognition, and modern DevOps practices. Leverage AI tools (GitHub Copilot, Qodo, GPT-5, Claude 4.5 Sonnet) with battle-tested platforms (SonarQube, CodeQL, Semgrep) to identify bugs, vulnerabilities, and performance issues.

Systematic 9-phase audit for claude-skills covering standards, docs verification, code accuracy, and version drift. \n \n Validates YAML structure, keywords, third-person style, and directory organization against skill standards \n Verifies API patterns, imports, and code examples against official documentation, GitHub repos, and npm packages \n Cross-checks consistency between SKILL.md and README.md, detects stale dependencies (>90 days), and identifies breaking changes \n Categorizes issues by

Comprehensive guide for evaluating iOS, macOS, tvOS, watchOS, and visionOS app code against Apple's App Store Review Guidelines. This skill covers EVERY guideline point to identify potential rejection issues before submission.

Technical rigor in code review: receiving feedback critically, requesting systematic reviews, and verifying before any completion claims. \n \n Three core practices: receiving feedback with technical evaluation over performative agreement, requesting reviews via code-reviewer subagent, and verification gates requiring evidence before status claims \n Includes decision tree and protocols for handling feedback from human partners versus external reviewers, with explicit rules against performative

Comprehensive App Store review preparation guide covering rejections, privacy manifests, IAP rules, and compliance checklists. \n \n Covers top rejection reasons (incomplete apps, inaccurate metadata, private API usage) with prevention strategies and real examples of approved vs. rejected content \n Detailed privacy manifest requirements with reason codes, ATT implementation patterns, and cross-reference checks between nutrition labels and actual data collection \n In-App Purchase and StoreKit r

Review requirements or plan documents through multi-persona analysis. Dispatches specialized reviewer agents in parallel, auto-fixes quality issues, and presents strategic questions for user decision.

Systematic checklist for reviewing code across functionality, security, performance, and maintainability. \n \n Covers six review areas: context understanding, functionality verification, code quality assessment, security checks, performance analysis, and test coverage validation \n Includes concrete examples of common issues (SQL injection, missing validation, unclear naming) paired with corrected versions \n Provides pre-review, per-section, and git-specific checklists to ensure nothing is mis

Identify and review overdue Google Tasks requiring immediate attention. \n \n Requires the gws-tasks skill to query Google Tasks API \n Three-step workflow: list all task lists, filter incomplete tasks by list ID, and review due dates for prioritization \n Returns task data in table format for easy scanning of overdue items \n

Peer review is a systematic process for evaluating scientific manuscripts. Assess methodology, statistics, design, reproducibility, ethics, and reporting standards. Apply this skill for manuscript and grant review across disciplines with constructive, rigorous evaluation.