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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

Navigate Rust code using Language Server Protocol for definitions, references, and symbol information. \n \n Supports three core LSP operations: go to definition, find references, and hover information for type/documentation lookup \n Handles workspace symbol search with disambiguation when multiple results exist, plus file-specific navigation with line numbers \n Includes error handling for missing rust-analyzer, typos, and generics/macros that produce multiple definitions \n Output formatted a

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

Autonomously scan and transform entire codebases into production-grade, enterprise-ready quality. \n \n Performs comprehensive line-by-line analysis across security, performance, architecture, code quality, and testing gaps without user prompts \n Automatically fixes critical issues including SQL injection, hardcoded secrets, weak authentication, N+1 queries, and architectural problems like circular dependencies and god classes \n Adds production infrastructure including structured logging, erro

Establish bidirectional links between Figma design components and code implementations using Code Connect. \n \n Requires Figma MCP server connection and published components on Organization or Enterprise plans \n Automatically identifies unmapped components in Figma selections, then scans your codebase for matching code components by name, structure, and props \n Presents matched components to you for review before creating mappings, allowing selective acceptance or rejection \n Supports multip

Expert code review of current git changes with a senior engineer lens. \n \n Detects SOLID violations (SRP, OCP, LSP, ISP, DIP), architecture smells, and proposes incremental refactors with clear rationale \n Scans for security risks including injection, XSS, AuthZ gaps, race conditions, and unsafe deserialization with exploitability assessment \n Identifies removal candidates and unused code with safe deletion vs. deferred plans and concrete follow-up checkpoints \n Flags code quality issues: e

Custom security implementations for authentication, authorization, input validation, and OWASP Top 10 vulnerability prevention. \n \n Covers password hashing (bcrypt/argon2), parameterized SQL queries, JWT validation, and rate limiting with explicit code examples \n Includes validation checkpoints for authentication (brute-force, session fixation, token expiration), authorization (privilege escalation), input handling (SQL injection, XSS), and security headers \n Enforces must-do constraints: ha

CLI tools for Svelte 5 documentation lookup and code analysis with built-in autofixer. \n \n Three core commands: list-sections to browse available docs, get-documentation to fetch full documentation for specific topics, and svelte-autofixer to analyze code and suggest fixes \n Autofixer supports Svelte 4 and 5 targeting via --svelte-version flag and async mode via --async option \n Accepts both inline code (with escaped $ characters) and file paths for analysis \n Designed for use within the sv

Structured code review framework covering quality, security, performance, and testing standards. \n \n Provides eight-step review methodology: context understanding, high-level architecture assessment, detailed code inspection, security audit, performance analysis, testing validation, documentation check, and constructive feedback delivery \n Covers SOLID principles, naming conventions, error handling, input validation, authentication/authorization, SQL injection and XSS prevention, and resource

Refactor Python scripts into beginner-friendly projects with instructional comments and markdown tutorials. \n \n Applies PEP 8 style guide compliance and standard Python best practices to improve code quality \n Adds instructional comments throughout the code explaining logic, reasoning, and importance for learners \n Generates a complete README.md tutorial with project overview, setup instructions, code breakdown, usage examples, and sample output \n Renames unclear variables and functions for