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Claude Skills by carlopezzuto
github.com/carlopezzuto32 skills0 installs50 views
- Api Design PrinciplesMaster REST and GraphQL API design principles to build intuitive, scalable, and maintainable APIs that delight developers. Use when designing new APIs, reviewing API specifications, or establishing API design standards.Votes: 0GitHub stars: 3
- Architecture PatternsImplement proven backend architecture patterns including Clean Architecture, Hexagonal Architecture, and Domain-Driven Design. Use when architecting complex backend systems or refactoring existing applications for better maintainability.Votes: 0GitHub stars: 3
- Async Python PatternsMaster Python asyncio, concurrent programming, and async/await patterns for high-performance applications. Use when building async APIs, concurrent systems, or I/O-bound applications requiring non-blocking operations.Votes: 0GitHub stars: 3
- Auth Implementation PatternsMaster authentication and authorization patterns including JWT, OAuth2, session management, and RBAC to build secure, scalable access control systems. Use when implementing auth systems, securing APIs, or debugging security issues.Votes: 0GitHub stars: 3
- Bash Defensive PatternsMaster defensive Bash programming techniques for production-grade scripts. Use when writing robust shell scripts, CI/CD pipelines, or system utilities requiring fault tolerance and safety.Votes: 0GitHub stars: 3
- Bats Testing PatternsMaster Bash Automated Testing System (Bats) for comprehensive shell script testing. Use when writing tests for shell scripts, CI/CD pipelines, or requiring test-driven development of shell utilities.Votes: 0GitHub stars: 3
- Code Review ExcellenceMaster effective code review practices to provide constructive feedback, catch bugs early, and foster knowledge sharing while maintaining team morale. Use when reviewing pull requests, establishing review standards, or mentoring developers.Votes: 0GitHub stars: 3
- Condition Based WaitingUse when tests have race conditions, timing dependencies, or inconsistent pass/fail behavior - replaces arbitrary timeouts with condition polling to wait for actual state changes, eliminating flaky tests from timing guessesVotes: 0GitHub stars: 3
- Debugging StrategiesMaster systematic debugging techniques, profiling tools, and root cause analysis to efficiently track down bugs across any codebase or technology stack. Use when investigating bugs, performance issues, or unexpected behavior.Votes: 0GitHub stars: 3
- Defense In DepthUse when invalid data causes failures deep in execution, requiring validation at multiple system layers - validates at every layer data passes through to make bugs structurally impossibleVotes: 0GitHub stars: 3
- Distributed TracingImplement distributed tracing with Jaeger and Tempo to track requests across microservices and identify performance bottlenecks. Use when debugging microservices, analyzing request flows, or implementing observability for distributed systems.Votes: 0GitHub stars: 3
- E2e Testing PatternsMaster end-to-end testing with Playwright and Cypress to build reliable test suites that catch bugs, improve confidence, and enable fast deployment. Use when implementing E2E tests, debugging flaky tests, or establishing testing standards.Votes: 0GitHub stars: 3
- Error Handling PatternsMaster error handling patterns across languages including exceptions, Result types, error propagation, and graceful degradation to build resilient applications. Use when implementing error handling, designing APIs, or improving application reliability.Votes: 0GitHub stars: 3
- Fastapi TemplatesCreate production-ready FastAPI projects with async patterns, dependency injection, and comprehensive error handling. Use when building new FastAPI applications or setting up backend API projects.Votes: 0GitHub stars: 3
- Grafana DashboardsCreate and manage production Grafana dashboards for real-time visualization of system and application metrics. Use when building monitoring dashboards, visualizing metrics, or creating operational observability interfaces.Votes: 0GitHub stars: 3
- Langchain ArchitectureDesign LLM applications using the LangChain framework with agents, memory, and tool integration patterns. Use when building LangChain applications, implementing AI agents, or creating complex LLM workflows.Votes: 0GitHub stars: 3
- Llm EvaluationImplement comprehensive evaluation strategies for LLM applications using automated metrics, human feedback, and benchmarking. Use when testing LLM performance, measuring AI application quality, or establishing evaluation frameworks.Votes: 0GitHub stars: 3
- Microservices PatternsDesign microservices architectures with service boundaries, event-driven communication, and resilience patterns. Use when building distributed systems, decomposing monoliths, or implementing microservices.Votes: 0GitHub stars: 3
- Ml Pipeline WorkflowBuild end-to-end MLOps pipelines from data preparation through model training, validation, and production deployment. Use when creating ML pipelines, implementing MLOps practices, or automating model training and deployment workflows.Votes: 0GitHub stars: 3
- Monorepo ManagementMaster monorepo management with Turborepo, Nx, and pnpm workspaces to build efficient, scalable multi-package repositories with optimized builds and dependency management. Use when setting up monorepos, optimizing builds, or managing shared dependencies.Votes: 0GitHub stars: 3
- Prometheus ConfigurationSet up Prometheus for comprehensive metric collection, storage, and monitoring of infrastructure and applications. Use when implementing metrics collection, setting up monitoring infrastructure, or configuring alerting systems.Votes: 0GitHub stars: 3
- Prompt Engineering PatternsMaster advanced prompt engineering techniques to maximize LLM performance, reliability, and controllability in production. Use when optimizing prompts, improving LLM outputs, or designing production prompt templates.Votes: 0GitHub stars: 3
- Python PackagingCreate distributable Python packages with proper project structure, setup.py/pyproject.toml, and publishing to PyPI. Use when packaging Python libraries, creating CLI tools, or distributing Python code.Votes: 0GitHub stars: 3
- Python Testing PatternImplement comprehensive testing strategies with pytest, fixtures, mocking, and test-driven development. Use when writing Python tests, setting up test suites, or implementing testing best practices.Votes: 0GitHub stars: 3
- Rag ImplementationBuild Retrieval-Augmented Generation (RAG) systems for LLM applications with vector databases and semantic search. Use when implementing knowledge-grounded AI, building document Q&A systems, or integrating LLMs with external knowledge bases.Votes: 0GitHub stars: 3
- Root Cause TracingUse 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 behaviorVotes: 0GitHub stars: 3
- Security ReviewUse this skill when adding authentication, handling user input, working with secrets, creating API endpoints, or implementing payment/sensitive features. Provides comprehensive security checklist and patterns.Votes: 0GitHub stars: 3
- Shellcheck ConfigurationMaster ShellCheck static analysis configuration and usage for shell script quality. Use when setting up linting infrastructure, fixing code issues, or ensuring script portability.Votes: 0GitHub stars: 3
- Tdd WorkflowUse this skill when writing new features, fixing bugs, or refactoring code. Enforces test-driven development with 80%+ coverage including unit, integration, and E2E tests.Votes: 0GitHub stars: 3
- Testing Anti PatternsUse when writing or changing tests, adding mocks, or tempted to add test-only methods to production code - prevents testing mock behavior, production pollution with test-only methods, and mocking without understanding dependenciesVotes: 0GitHub stars: 3
- Verification Before CompletionUse when about to claim work is complete, fixed, or passing, before committing or creating PRs, when task are finished - requires running verification commands and confirming output before making any success claims; evidence before assertions alwaysVotes: 0GitHub stars: 3
- Python Performance OptimizationProfile and optimize Python code using cProfile, memory profilers, and performance best practices. Use when debugging slow Python code, optimizing bottlenecks, or improving application performance.Votes: 0GitHub stars: 3