Which libraries and frameworks can I look up?

It supports a vast range of ecosystems including React, Next.js, Express, Prisma, MongoDB, Fastify, NestJS, Vue.js, Svelte, and major languages like Python, Go, and Rust.

Can I get conceptual explanations instead of just code snippets?

Yes. By using the '--mode info' parameter, the skill shifts its filtering focus from pure code examples to conceptual explanations and framework architecture.

How does Context7 achieve such high token savings?

It utilizes a shell pipeline (awk/grep/sed) to process raw documentation in a subprocess. This extracts only the essential code blocks and API signatures, ensuring only the most relevant 20% of data enters Claude's context window.

Why is this better than standard documentation MCP tools?

Standard tools often dump thousands of tokens of prose into your chat history, which quickly hits context limits. This skill provides the same utility while using roughly 77-86% fewer tokens per query.

Context7 Efficient Documentation Fetcher

Name: Context7 Efficient Documentation Fetcher
Author: alijilani-dev

byalijilani-dev

学习与文档

Retrieves and filters library documentation with up to 86% token savings for highly optimized AI-assisted coding.

关于

Context7 Efficient is a specialized Claude Code skill designed to retrieve high-quality library documentation, API references, and code examples while minimizing token consumption. By utilizing a sophisticated shell pipeline to filter out verbose prose and retain only critical code signatures and examples, it allows Claude to access technical context for frameworks like React, Next.js, and Prisma without bloating the conversation history. This skill is essential for developers who need accurate technical references while maintaining long-running, cost-effective, and performance-focused AI coding sessions.

主要功能

Automatic library resolution and ID-based direct lookup for speed
Token-efficient documentation retrieval with 77-86% context savings
0 GitHub stars
Intelligent shell pipeline filtering for code snippets and API signatures
Wide support for JavaScript, Python, Go, Rust, and popular frameworks
Switchable modes for code-heavy examples or conceptual documentation

使用场景

Troubleshooting specific library API signatures and implementation patterns efficiently
Learning and implementing new frameworks like Prisma or Fastify using filtered best practices
Quickly fetching React hook examples or Next.js routing syntax without context bloat

关于

主要功能

Automatic library resolution and ID-based direct lookup for speed
Token-efficient documentation retrieval with 77-86% context savings
0 GitHub stars
Intelligent shell pipeline filtering for code snippets and API signatures
Wide support for JavaScript, Python, Go, Rust, and popular frameworks
Switchable modes for code-heavy examples or conceptual documentation

使用场景

Troubleshooting specific library API signatures and implementation patterns efficiently
Learning and implementing new frameworks like Prisma or Fastify using filtered best practices
Quickly fetching React hook examples or Next.js routing syntax without context bloat