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Context-driven code reviews prioritizing quality, security, testability, and maintainability. \n \n Organizes feedback into four priority levels: blockers (must fix), major issues (should fix), minor improvements, and suggestions, with clear templates and rationale for each \n Covers five core review areas: logic correctness, security risks, test coverage, performance issues, and error handling; explicitly excludes style nitpicking and formatting \n Recommends reviewing code in chunks under 400

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Convert UI screenshots into production-ready code with accurate styling and structure.

Static analysis security scanner that identifies OWASP vulnerabilities across backend, frontend, mobile, and library code. \n \n Scans for SQL injection, XSS, BOLA, BFLA, SSRF, prototype pollution, unsafe deserialization, ReDoS, path traversal, and zip slip vulnerabilities \n Three scan depths available: quick (default), balanced, and full, with token usage warnings for comprehensive scans \n Automated workflow: plans vulnerability vectors per project type, nominates candidate files, analyzes fi

Comprehensive code review for diffs with auto-detected domain-specific checks. \n \n Analyzes changed code for security vulnerabilities, anti-patterns, quality issues, and breaking changes across generic, frontend, and backend domains \n Auto-detects domain (frontend, backend, CLI, config) from file paths and applies relevant checklists \n Generates structured markdown reports with severity levels, file locations, code snippets, and actionable recommendations \n Performs impact analysis to ident

Technology-agnostic prompt generator for identifying and documenting high-quality code exemplars across multiple languages. \n \n Supports seven programming languages (.NET, Java, JavaScript, TypeScript, React, Angular, Python) with auto-detection capability \n Configurable analysis depth (Basic, Standard, Comprehensive), categorization method (Pattern Type, Architecture Layer, File Type), and documentation format \n Generates exemplars.md files with real file references, descriptions, and optio

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

Comprehensive guide to code generation techniques including template engines, AST manipulation, code scaffolding, and automated boilerplate generation for increased productivity and consistency.

Verifies code implements exactly what documentation specifies for blockchain audits. \n \n Performs deterministic, line-by-line semantic analysis of code against specification documents, whitepapers, or design docs to identify gaps and misalignments \n Extracts specification intent and code behavior into structured intermediate representations (Spec-IR, Code-IR, Alignment-IR) with full traceability and confidence scores \n Classifies divergences by severity (critical, high, medium, low) with evi

Analyzes code diffs and files to identify bugs, security vulnerabilities, performance issues, and architectural concerns with prioritized feedback. \n \n Detects common issues including SQL injection, XSS, N+1 queries, magic numbers, hardcoded secrets, and design pattern violations \n Follows a structured five-step workflow: context understanding, architecture review, code quality checks, test validation, and categorized reporting \n Produces prioritized reports organized by severity (critical,