发现 data ai debugging 相关 Skills，比较来源仓库和用途，查看适合你工作流的技能说明。
Comprehensive frontend architecture analyzer that identifies technology stacks, build tools, and architectural patterns. Use when you need to quickly understand a project's structure, dependencies, and technica...
Enhanced dependency analyzer with comprehensive markdown reporting and actionable recommendations. Use when you need to optimize frontend project dependencies, detect security vulnerabilities, identify unused p...
Review code for quality, bugs, security issues, and best practices. Use this skill when the user asks for code review, code analysis, or wants feedback on their code.
WHEN: Pandas/NumPy code review, data processing, vectorization, memory optimization WHAT: Vectorization patterns + Memory efficiency + Data validation + Performance optimization + Best practices WHEN NOT: Web f...
WHEN: Flask project review, Blueprint structure, extensions, request handling WHAT: Blueprint organization + Extension patterns + Request/response handling + Configuration + Testing WHEN NOT: FastAPI → fastapi-...
WHEN: Coverage analysis, finding untested files, test prioritization, coverage gap identification WHAT: Line/Branch/Function coverage + untested file list + priority by importance + improvement roadmap WHEN NOT...
WHEN: Rust project review, ownership/borrowing, error handling, unsafe code, performance WHAT: Ownership patterns + Lifetime analysis + Error handling (Result/Option) + Unsafe audit + Idiomatic Rust WHEN NOT: R...
WHEN: Performance analysis, bundle size optimization, rendering, Core Web Vitals, code splitting WHAT: Bundle analysis + large dependency detection + re-render issues + useMemo/useCallback suggestions + LCP/FID...
WHEN: SQL query review, query optimization, index usage, N+1 detection, performance analysis WHAT: Query plan analysis + Index recommendations + N+1 detection + Join optimization + Performance tuning WHEN NOT:...
Expert in Python 3.10+ fundamentals and best practices for the Drift project including import ordering (isort), code organization, and PEP 8 conventions. Use when writing or reviewing Python code.
Plans pytest test strategies for Drift's 90%+ coverage requirement using coverage analysis, edge case identification, and test suite design. Use when determining what tests to write, analyzing coverage gaps, or...
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 o...
Analyzes your recent coding chat history to identify patterns, development gaps, and areas for improvement, curates relevant learning resources from HackerNews, and automatically sends a personalized growth rep...
Toolkit for interacting with and testing local web applications using Playwright. Supports verifying frontend functionality, debugging UI behavior, capturing browser screenshots, and viewing browser logs.
Analyze a project to provide a summary of line counts per programming language (e.g., how many lines of Go vs Rust). Generates a PDF summary report.
Detects violations of Clean Code principles and suggests refactorings. Use when reviewing code quality, improving readability, or refactoring methods, classes, and modules.
Measures and limits cognitive load in Jakarta EE/MicroProfile code. Use when reviewing code complexity, designing services/entities, or identifying when to extract abstractions.
フロントエンドとバックエンドのデバッグを支援します。エラーの原因特定、ログの確認、型エラーの修正、実行時エラーの解析、Tauri 通信のデバッグなどに使用します。
⚡ PRIMARY TOOL for: 'what's tested', 'find test coverage', 'audit test quality', 'missing tests', 'edge cases', 'test patterns'. Uses claudemem v0.3.0 AST with callers analysis for test discovery. GREP/FIND/GL...
⚡ PRIMARY TOOL for semantic code search AND structural analysis. NEW: AST tree navigation with map, symbol, callers, callees, context commands. PageRank ranking. ANTI-PATTERNS: Reading files without mapping, G...
Multi-agent code analysis orchestration using claudemem. Share claudemem output across parallel agents. Enables parallel investigation, consensus analysis, and role-based command mapping.
This skill should be used when the user asks about "R2", "D1", "KV", "Durable Objects", "Queues", "Vectorize", "Hyperdrive", "Workers Analytics", "Email Routing", "Browser Rendering", or discusses Cloudflare pl...
⚡ PRIMARY TOOL for: 'why is X broken', 'find bug source', 'root cause analysis', 'trace error', 'debug issue', 'find where X fails'. Uses claudemem v0.3.0 AST with context command for call chain analysis. GREP...
⚡ PRIMARY TOOL for: 'what's the architecture', 'system design', 'how are layers organized', 'find design patterns', 'audit structure', 'map dependencies'. Uses claudemem v0.3.0 AST structural analysis with Pag...
默认按已收录数据中的 GitHub 仓库 Stars 排序。Stars 属于来源仓库，同一仓库的多个技能可能共享相同数值；它反映仓库关注度，不代表单个技能的安装量或质量评分。