implementing-api-patterns
Select and implement the optimal API pattern for your backend needs. This skill guides you through REST, GraphQL, gRPC, and tRPC with framework recommendations for Python, TypeScript, Rust, and Go, plus pagination, caching, rate limiting, and OpenAPI documentation strategies.
Implementing API Patterns helps you select the right API architecture and framework for your specific backend requirements.
AI-generated summary based on this skill's SKILL.md
Decision gist · record as of 2025-12-11
Implementing API Patterns helps you select the right API architecture and framework for your specific backend requirements. Select and implement the optimal API pattern for your backend needs. This skill guides you through REST, GraphQL, gRPC, and tRPC with framework recommendations for Python, TypeScript, Rust, and Go, plus pagination, caching, rate limiting, and OpenAPI documentation strategies.
Use it when
- implementing-api-patterns compares GraphQL vs REST to help you decide.
- implementing-api-patterns covers pagination approaches including cursor-based and offset-based methods.
Verify before relying
Read SKILL.md below before installing (25 files). Open directory: indexed for reading, not audited.
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ancoleman/ai-design-components/implementing-api-patterns · repository language: Python
Open directory. Skills are indexed for reading, not audited. Review a skill's body before installing it.
Frequently asked questions
AI-generated answers based on this skill's SKILL.md and metadata
How do I build a REST API with FastAPI?
implementing-api-patterns guides you through building REST APIs using FastAPI, a modern Python framework that automatically generates OpenAPI documentation. FastAPI provides decorators for defining endpoints, automatic request validation, and built-in support for async operations. The skill covers structuring your routes, handling different HTTP methods, and leveraging FastAPI's Swagger UI integration for interactive API documentation.
Should I choose GraphQL or REST for my backend?
implementing-api-patterns compares GraphQL vs REST to help you decide. REST is ideal for simple, resource-oriented APIs with predictable access patterns. GraphQL excels when frontends need flexible data fetching, reducing over-fetching and under-fetching. The skill explains trade-offs in complexity, caching, and tooling, helping you select based on your use case, team expertise, and performance requirements.
What are the best API pagination strategies?
implementing-api-patterns covers pagination approaches including cursor-based and offset-based methods. Cursor-based pagination is more efficient for large datasets and handles insertions better, while offset-based is simpler to implement. The skill explains when to use each, how to implement them across REST and GraphQL, and best practices for maintaining consistency and performance.
How do I add rate limiting and caching to my API?
implementing-api-patterns teaches rate limiting using token bucket algorithms and sliding windows, plus HTTP caching strategies. You'll learn to implement rate limiting middleware, set appropriate cache headers, and use tools like Redis for distributed caching. The skill covers both client-side and server-side approaches to protect your API and improve performance.
Which framework should I use for high-performance APIs?
implementing-api-patterns recommends frameworks based on your language: FastAPI for Python, Axum for Rust, Gin for Go, and Hono for edge computing. Each excels in different contexts—Rust's Axum and async-graphql offer extreme performance, Go's Gin provides simplicity and speed, while Hono targets serverless and edge environments. The skill helps match framework choice to your performance and deployment needs.
How do I implement gRPC for microservices communication?
implementing-api-patterns covers gRPC setup for high-performance service-to-service communication. You'll learn protocol buffers for defining services, implementing gRPC servers in languages like Rust (Tonic) and Go, and using connect-go for browser compatibility. The skill explains when gRPC outperforms REST, how to structure microservices, and strategies for versioning and backward compatibility.
SKILL.md
Rendered from the published skill. Quoted content, verbatim.
API Patterns Skill
Purpose
Design and implement APIs using the optimal pattern and framework for the use case. Choose between REST, GraphQL, gRPC, and tRPC based on API consumers, performance requirements, and type safety needs.
When to Use This Skill
Use when: - Building backend APIs for web, mobile, or service consumers - Connecting frontend components (forms, tables, dashboards) to databases - Implementing pagination, rate limiting, or caching strategies - Generating OpenAPI documentation automatically - Choosing between REST, GraphQL, gRPC, or tRPC patterns - Integrating
(truncated - see the full file via the links below)
File tree — 15 files
skills/implementing-api-patterns/README.md
skills/implementing-api-patterns/SKILL.md
skills/implementing-api-patterns/examples/go-gin/README.md
skills/implementing-api-patterns/examples/graphql-strawberry/README.md
skills/implementing-api-patterns/examples/grpc-tonic/README.md
skills/implementing-api-patterns/examples/python-fastapi/README.md
skills/implementing-api-patterns/examples/python-fastapi/main.py
skills/implementing-api-patterns/examples/python-fastapi/requirements.txt
skills/implementing-api-patterns/examples/rust-axum/README.md
skills/implementing-api-patterns/examples/typescript-hono/index.ts
skills/implementing-api-patterns/examples/typescript-hono/package.json
skills/implementing-api-patterns/examples/typescript-trpc/README.md
skills/implementing-api-patterns/outputs.yaml
skills/implementing-api-patterns/references/caching-patterns.md
skills/implementing-api-patterns/references/graphql-schema-design.md
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