smart-debugging

AI-powered intelligent debugging with stack trace analysis, error pattern recognition, and automated fix suggestions. Use when debugging complex errors, analyzing stack traces, or performing root cause analysis. Triggers: 'debug', 'error analysis', 'stack trace', 'root cause', 'troubleshooting'.

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Repositório: greyhaven-ai/claude-code-config
Última atividade na origem: 17 de abril de 2026 às 23:11
Idioma detectado do SKILL.md: inglês
Estrelas: 29
Forks: 5

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npx skills add https://github.com/greyhaven-ai/claude-code-config --skill smart-debugging

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SKILL.md

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name: smart-debugging
description: AI-powered intelligent debugging with stack trace analysis, error pattern recognition, and automated fix suggestions. Use when debugging complex errors, analyzing stack traces, or performing root cause analysis. Triggers: 'debug', 'error analysis', 'stack trace', 'root cause', 'troubleshooting'.
skills: ["code-style","testing-strategy","incident-response"]
allowed-tools: ["Read","Write","MultiEdit","Bash","Grep","Glob","TodoWrite"]

# Smart Debugging Skill AI-powered intelligent debugging with stack trace analysis, error pattern recognition, and automated fix suggestions. ## Description Systematic error diagnosis through triage, investigation, root cause analysis, fix generation, and prevention strategies. ## What's Included - **Examples**: Stack trace analysis, error pattern fixes - **Reference**: Debugging methodologies, common errors - **Templates**: Debug report templates, RCA structures ## Use When - Systematic error diagnosis needed - Stack traces to analyze - Root cause investigation - Automated fix suggestions ## Related Agents - `smart-debug` **Skill Version**: 1.0

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code-quality-analysis

Multi-mode code quality analysis covering security reviews (OWASP Top 10), clarity refactoring (readability rules), synthesis analysis (cross-file issues), and DDD/DRY lenses (flags mechanical naming, primitive obsession, domain rules leaking into infrastructure, and premature abstractions via the three-occurrences-same-concept rule). Supports team-mode parallel analysis when invoked from quality-pipeline. Use when reviewing code for security vulnerabilities, improving code readability, conducting quality audits, pre-deployment checks, or when user mentions 'code quality', 'code review', 'security review', 'refactoring', 'code smell', 'OWASP', 'code clarity', 'primitive obsession', 'value object', 'ubiquitous language', 'DRY', 'premature abstraction', or 'quality audit'.

2026-04-19

performance-optimization

Comprehensive performance analysis and optimization for algorithms (O(n²)→O(n)), databases (N+1 queries, indexes), React (memoization, virtual lists), bundles (code splitting), API caching, and memory leaks. 85%+ improvement rate. Use when application is slow, response times exceed SLA, high CPU/memory usage, performance budgets needed, or when user mentions 'performance', 'slow', 'optimization', 'bottleneck', 'speed up', 'latency', 'memory leak', or 'performance tuning'.

2026-04-19

api-design-standards

Design RESTful APIs following Grey Haven standards - FastAPI routes, Pydantic schemas, HTTP status codes, pagination, filtering, error responses, OpenAPI docs, and multi-tenant patterns. Use when creating API endpoints, designing REST resources, implementing server functions, configuring FastAPI, writing Pydantic schemas, setting up error handling, implementing pagination, or when user mentions 'API', 'endpoint', 'REST', 'FastAPI', 'Pydantic', 'server function', 'OpenAPI', 'pagination', 'validation', 'error handling', 'rate limiting', 'CORS', or 'authentication'.

2026-04-19

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smart-debugging

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