API Development Claude 스킬

gRPC Python Services

Implements high-performance microservice communication using gRPC and Protocol Buffers for Python-based backend systems.

LLM Streaming Patterns

Implements high-performance real-time token streaming and Server-Sent Events (SSE) for AI-powered applications.

Type Safety & Validation Patterns

Implements end-to-end type safety and runtime validation using Zod, tRPC, and Prisma for robust TypeScript and Python applications.

LangGraph Functional API

Simplifies AI workflow development using Python decorators for orchestration, parallel execution, and state persistence.

FastAPI Advanced Patterns

Implements production-ready FastAPI architectures including lifespan management, dependency injection, and specialized middleware.

System Design Interrogation

Guides system architecture planning through structured questions across scalability, security, data, and operational dimensions.

LLM Function Calling & Tool Use

Implements production-ready tool calling patterns and structured output schemas for AI agents.

Connection Pooling for Python

Optimizes database and HTTP performance using production-ready async connection pooling patterns for Python applications.

Streaming API Patterns

Implements production-ready real-time data streaming using Server-Sent Events (SSE), WebSockets, and ReadableStream APIs.

Strawberry GraphQL Development

Builds type-safe, production-ready GraphQL APIs using the Strawberry library and FastAPI integration.

RFC 9457 API Error Handling

Implements RFC 9457 Problem Details to provide standardized, machine-readable HTTP API error responses for modern backend services.

Temporal.io Workflow Orchestration

Orchestrates durable, fault-tolerant distributed applications using Temporal.io for complex, long-running business processes.

LangGraph State & Persistence

Manages persistent workflow states, fault-tolerant execution recovery, and multi-threaded conversation memory for LangGraph agents.

Transactional Outbox Pattern

Implements reliable, atomic event publishing to ensure consistency between database state and message brokers.

Clean Architecture & DDD Patterns

Implements maintainable, decoupled backend systems using SOLID principles, hexagonal architecture, and Domain-Driven Design (DDD).

Advanced Python Asyncio Patterns

Implements high-performance Python concurrency using modern structured patterns, TaskGroups, and robust error handling for Python 3.11+ applications.

System Design Interrogation

Evaluates architectural plans across five critical dimensions to prevent technical debt and scalability issues before implementation.

Saga Patterns for Distributed Transactions

Implements robust saga patterns to manage distributed transactions and maintain consistency across microservices through orchestration and choreography.

Aggregate Design Patterns

Implements Domain-Driven Design (DDD) aggregate patterns to maintain data consistency and enforce business invariants in complex backend systems.

Advanced TanStack Query v5

Implements high-performance data fetching, caching, and optimistic UI updates using TanStack Query v5 best practices.

Resilience Patterns

Implements production-grade fault tolerance and resilience patterns for distributed systems and LLM-based workflows.

Backend Architecture Enforcer

Enforces FastAPI Clean Architecture principles by validating layer separation and dependency injection patterns in real-time.

RFC 9457 API Error Handling

Standardizes HTTP API error responses using the machine-readable RFC 9457 Problem Details format for robust backend services.

Strawberry GraphQL Patterns

Builds type-safe, production-ready GraphQL APIs in Python using Strawberry and FastAPI with advanced patterns for performance and scalability.

MCP Advanced Patterns

Implements production-grade Model Context Protocol patterns for high-performance tool orchestration and resource management.

Domain-Driven Design (DDD) Patterns

Models complex business logic using tactical DDD patterns including entities, value objects, and bounded contexts.

Message Queue Patterns

Implements high-performance asynchronous messaging and event-driven architectures using RabbitMQ, Kafka, and Redis Streams.

Advanced Python Asyncio

Implements high-performance Python concurrency using modern 3.11+ asyncio features and structured concurrency patterns.

Advanced MCP Patterns

Implements production-grade Model Context Protocol patterns for tool orchestration, resource lifecycle management, and horizontal scaling.

Resilience Patterns

Implements production-grade fault tolerance and reliability patterns for distributed systems and LLM integrations.