Descubre Habilidades de Claude para api development. Explora 83 habilidades y encuentra las capacidades perfectas para tus flujos de trabajo de IA.
Implements robust saga patterns to manage distributed transactions and maintain consistency across microservices through orchestration and choreography.
Develops custom Model Context Protocol (MCP) servers to extend Claude's capabilities with specialized tools, data resources, and prompt templates.
Simplifies AI workflow development using Python decorators for orchestration, parallel execution, and state persistence.
Orchestrates durable, fault-tolerant distributed applications using Temporal.io for complex, long-running business processes.
Provides comprehensive, production-ready design patterns and architectural standards for REST, GraphQL, and gRPC services.
Implements high-performance microservice communication using gRPC and Protocol Buffers for Python-based backend systems.
Implements end-to-end type safety and runtime validation using Zod, tRPC, and Prisma for robust TypeScript and Python applications.
Implements durable, fault-tolerant distributed workflows and saga patterns using the Temporal.io execution engine.
Optimizes database and HTTP connection lifecycles in high-concurrency Python asynchronous applications.
Implements exactly-once semantics and request deduplication for reliable distributed systems and APIs.
Implements high-performance server state management patterns for React using TanStack Query v5.
Optimizes database and HTTP performance using production-ready async connection pooling patterns for Python applications.
Implements production-ready FastAPI architectures including lifespan management, dependency injection, and specialized middleware.
Guides system architecture planning through structured questions across scalability, security, data, and operational dimensions.
Implements production-ready tool calling patterns and structured output schemas for AI agents.
Evaluates architectural plans across five critical dimensions to prevent technical debt and scalability issues before implementation.
Implements high-performance real-time token streaming and Server-Sent Events (SSE) for AI-powered applications.
Implements high-performance Python concurrency using modern structured patterns, TaskGroups, and robust error handling for Python 3.11+ applications.
Enforces FastAPI Clean Architecture principles by validating layer separation and dependency injection patterns in real-time.
Manages persistent workflow states, fault-tolerant execution recovery, and multi-threaded conversation memory for LangGraph agents.
Implements high-performance data fetching, caching, and optimistic UI updates using TanStack Query v5 best practices.
Standardizes the architecture and implementation of production-grade REST, GraphQL, and gRPC APIs using industry best practices.
Implements production-grade fault tolerance and reliability patterns for distributed systems and LLM integrations.
Implements production-grade Model Context Protocol patterns for tool orchestration, resource lifecycle management, and horizontal scaling.
Standardizes HTTP API error responses using the machine-readable RFC 9457 Problem Details format for robust backend services.
Builds type-safe, production-ready GraphQL APIs in Python using Strawberry and FastAPI with advanced patterns for performance and scalability.
Implements production-ready real-time data streaming using Server-Sent Events (SSE), WebSockets, and ReadableStream APIs.
Builds type-safe, production-ready GraphQL APIs using the Strawberry library and FastAPI integration.
Implements maintainable, decoupled backend systems using SOLID principles, hexagonal architecture, and Domain-Driven Design (DDD).
Implements Domain-Driven Design (DDD) aggregate patterns to maintain data consistency and enforce business invariants in complex backend systems.
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