review▌

AI-powered code review using CodeRabbit, triggered on explicit request or autonomously when quality/security issues are detected. \n \n Identifies bugs, security vulnerabilities, and quality risks; groups findings by severity (Critical, Warning, Info) \n Supports reviewing staged, committed, or all changes; can compare against specific branches or commit hashes \n Offers two output modes: --plain for detailed feedback with fix suggestions, or --prompt-only for minimal agent-optimized output \n E

Review a web app or page for visual design quality. This is not a UX audit (usability, workflow, friction) — this checks whether the design is professional, consistent, and polished.

Analyze, audit, and improve project structure.

Review pull requests against repository standards. Two-phase process: automated validation, then manual content review.

Systematic code review practices for constructive feedback, bug detection, and team knowledge sharing. \n \n Covers the complete review workflow: context gathering, high-level architecture assessment, line-by-line analysis, and decision-making with clear severity labeling (blocking, important, nit, suggestion) \n Includes language-specific patterns for Python, TypeScript, and JavaScript, plus specialized review techniques for security, testing, and architectural changes \n Provides templates, ch

Comprehensive code reviews covering quality, security, performance, and best practices. \n \n Systematic review process across five dimensions: code quality, security vulnerabilities, performance, testing, and maintainability \n Includes initial assessment, detailed analysis guides, and constructive feedback frameworks \n Covers pull request analysis, coding standards compliance, and developer mentoring through structured review \n Best practices emphasize respectful feedback with explanations a

Security-focused differential analysis of code changes with adaptive depth, blast radius calculation, and markdown reporting. \n \n Analyzes PRs, commits, and diffs across three codebase sizes (SMALL/MEDIUM/LARGE) with risk-first prioritization on auth, crypto, value transfer, and external calls \n Includes six-phase workflow: triage, code analysis, test coverage assessment, blast radius calculation, adversarial modeling, and comprehensive markdown report generation \n Detects security regressio

Comprehensive code analysis covering security vulnerabilities, performance bottlenecks, maintainability issues, and best practice violations. \n \n Scans for critical security flaws including SQL injection, XSS, authentication gaps, unsafe deserialization, and credential exposure \n Identifies performance problems such as N+1 queries, inefficient algorithms, memory leaks, and unnecessary re-renders \n Evaluates code quality across duplication, function length, cyclomatic complexity, naming clari

sentry-pr-code-review

Problem: Causes all nodes to re-mount on every render.