optimizing-performance
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
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.
response-analyzer
MCP Response Analyzer pattern - Write large responses to temp files, load summaries into context
reviewing-silent-failures
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.
web-application-reconnaissance
Systematic methodology for mapping web application attack surface, discovering hidden endpoints, and identifying technologies
mini-apps-debugging
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.
reviewing-silent-failures
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.
agentuity-cli-profile-current
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r3f-performance
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.
debug-troubleshoot
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.
root-cause-tracing
Use when errors occur deep in execution and you need to trace back to find the original trigger - systematically traces bugs backward through call stack, adding instrumentation when needed, to identify source of invalid data or incorrect behavior
swift-concurrency-expert
Swift Concurrency review and remediation for Swift 6.2+. Use when asked to review Swift Concurrency usage, improve concurrency compliance, or fix Swift concurrency compiler errors in a feature or file.
optimizing-code
Improve code performance without changing behavior. Use when code fails latency/throughput requirements. Covers profiling, caching, and algorithmic optimization.
audit-performance
Performance-focused audit that can run in background during implementation. Checks for inefficiencies, memory leaks, widget rebuilds. Injects P0 findings to main agent.
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior (including race conditions, deadlocks, concurrency issues) - four-phase framework (root cause investigation, pattern analysis, hypothesis testing, implementation) with specialized techniques for deep call stack tracing and concurrency debugging
gdpr-auditor
This skill should be used when analyzing codebases, applications, databases, or systems for GDPR (General Data Protection Regulation) compliance. Use this skill when users need to audit data protection practices, identify potential compliance issues, assess data handling procedures, review privacy policies, or ensure adherence to EU data protection requirements.
unity-performance
Optimize Unity game performance through profiling, draw call reduction, and resource management. Masters batching, LOD, occlusion culling, and mobile optimization. Use for performance bottlenecks, frame rate issues, or optimization strategies.
go-performance
Go performance optimization - profiling, benchmarks, memory management