pattern-detector
Universal pattern detector - learns from ANY codebase through sample analysis
Essential command-line tools and system utilities.
Universal pattern detector - learns from ANY codebase through sample analysis
Review Dart FFI code for security issues in cryptographic contexts. Use when reviewing code changes, checking for memory leaks, verifying secure memory handling, or auditing cryptographic code.
Debug memory leaks, profile memory usage, optimize allocations. Use when heap grows unexpectedly, OOM errors occur, or profiling shows memory bottleneck. Covers C++ (Valgrind, ASAN, RAII), Python (tracemalloc, objgraph), and general patterns.
Root cause analysis for software bugs using the 5 Whys technique. Use when the user wants to find the underlying cause of a bug, error, or technical issue. Triggers include phrases like "why is this happening", "root cause", "debug this", or when investigating software problems.
Methodical approach to finding security vulnerabilities through source code review and static analysis
Reduce token consumption by 70-80% when using Chrome DevTools MCP through smart snapshot strategies and optional Gemini Flash vision processing. Includes decision trees, pattern guides, and automated optimization workflows.
Automate Chrome browser via DevTools Protocol. Navigate pages, interact with elements, inspect network/console, analyze performance, and capture screenshots for web testing and automation tasks.
Visual element selector for extracting HTML, screenshots, and context from web pages. Use when you need to see what the user is referring to, when clarification is needed about UI elements, or when the user offers to show you something visually.
Frontend performance optimization with data-driven approach. Use when optimizing page load times, improving Web Vitals, or when user mentions performance, Web Vitals, LCP, FID, CLS, パフォーマンス最適化, 速度改善, bundle size.
Systematic debugging methodology emphasizing root cause analysis over quick fixes. Use when debugging complex issues, investigating production failures, or avoiding symptom-based patches in favor of understanding underlying problems.
MCP Response Analyzer pattern - Write large responses to temp files, load summaries into context
Silent failure detection patterns for frontend code. Triggers: silent failure, empty catch, エラーハンドリング, 握りつぶし, swallowed error.
Systematic methodology for mapping web application attack surface, discovering hidden endpoints, and identifying technologies
Debug and troubleshoot Mini-Apps when they fail to load, build, or run. Covers build checks, browser console inspection, bridge issues, and asset routing fixes.
Silent failure detection patterns for frontend code. Use when reviewing error handling, detecting swallowed errors, or when user mentions silent failure, empty catch, エラーハンドリング, 握りつぶし, swallowed error.
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R3F performance optimization—LOD (Level of Detail), frustum culling, instancing strategies, draw call reduction, frame budgets, lazy loading, and profiling tools. Use when optimizing render performance, handling large scenes, or debugging frame rate issues.
Systematic debugging approach for Rust async code with Tokio, Turso, and redb. Use when diagnosing runtime issues, performance problems, async deadlocks, database connection issues, or panics.