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。
Advanced coverage analysis with actionable insights. Use to identify coverage gaps, suggest specific tests, track coverage trends, and highlight critical uncovered code. Essential for reaching 80%+ coverage tar...
When Truth Layer identifies a blocker:
Logging, error messages, and debugging patterns for React. Use when adding logging, designing error messages, debugging production issues, or improving code observability. Works for both React web and React Nat...
Detect accidentally committed secrets, credentials, and sensitive information in code.
System diagnostics using GASP (General AI Specialized Process monitor). Use when user asks about Linux system performance, requests system checks, mentions GASP, asks to diagnose hosts, or says things like "che...
Systematic methodology for debugging bugs, test failures, and unexpected behavior. Use when encountering any technical issue before proposing fixes. Covers root cause investigation, pattern analysis, hypothesis...
Search code by AST structure using ast-grep. Find semantic patterns like function calls, imports, class definitions instead of text patterns. Triggers on: find all calls to X, search for pattern, refactor usage...
Deep architectural audit focused on finding dead code, duplicated functionality, architectural anti-patterns, type confusion, and code smells. Use when user asks for architectural analysis, find dead code, iden...
Use this skill when user asks to "review code", "check for issues", "analyze code quality", "find bugs", or wants feedback on code implementation.
Parse and analyze application logs to identify errors, patterns, and insights.
Operates and debugs the local stack (API/worker/frontend); focuses on observability, logs, and safe automation.
Search and retrieve context from past development sessions using Chronicle data. Works with MCP (fast, structured) or CLI commands (portable). Use when user asks about previous work, wants to recall past decisi...
Guide for writing effective log messages using wide events / canonical log lines. Use when writing logging code, adding instrumentation, improving observability, or reviewing log statements. Teaches high-cardin...
Comprehensive audit of Expo/React Native app API integration layer. Use when asked to: (1) Review API interactions, auth handling, or token management, (2) Find hardcoded data or screens bypassing API, (3) Veri...
Comprehensive dependency mapping, analysis, and visualization tool for software projects
Four-phase debugging framework that ensures root cause identification before fixes. Use when encountering bugs, test failures, unexpected behavior, or when previous fix attempts failed. Enforces investigate-fir...
Analyzes a codebase and suggests custom Claude Code skills and subagents to improve development workflow. Use when user wants tooling suggestions, automation ideas, or asks "what skills would help this project"...
Generic AIOps (AI for IT Operations) patterns and best practices for 2025. Provides comprehensive implementation strategies for intelligent monitoring, automation, incident response, and observability across an...
Reviews code for quality, security, performance, and accessibility issues. Use when user mentions レビュー, review, コードレビュー, セキュリティ, パフォーマンス, 品質チェック, セルフレビュー, PR, diff, 変更確認...
Automated code review with best practices, security checks, and quality standards.
Automatically find relevant context from knowledge graph and code relationships while coding. Detects when context would be helpful (new files, unfamiliar code, architectural decisions) and surfaces related ent...
Comprehensive code review expertise. Use when reviewing code, evaluating architecture, or assessing quality. Triggers on review, evaluate, assess, audit, code quality, best practices.
Detect design patterns and anti-patterns in code with recommendations.
Debug React Native apps including metro bundler issues, native errors, performance problems, and crash analysis. Use when troubleshooting errors or investigating issues.
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。