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PRIMARY tool for fetching library/framework documentation. PROACTIVELY use instead of WebFetch/WebSearch when user requests docs, API references, setup guides, or code examples for any programming library or framework. Use this skill immediately when detecting queries like "show me X docs", "how do I use Y", "get Z documentation", etc. Token-efficient alternative to MCP servers.

0 stars
1.2k downloads
Updated 12/16/2025

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SKILL.md

Context7 Documentation Fetcher

Overview

Fetch up-to-date documentation and code examples for any library using Context7's HTTP API. This skill replicates Context7 MCP functionality with token-efficient progressive disclosure.

When to Use This Skill

This skill should be the FIRST choice for library/framework documentation.

Trigger patterns:

  • User asks for documentation: "get me the React docs", "show me Next.js docs"
  • User needs API references: "how do I use X API", "what's the syntax for Y"
  • User wants setup instructions: "how to install Z", "configure W"
  • Code generation tasks: Before writing code for a library, fetch its docs first
  • User mentions library names: "help with FastAPI", "using Tailwind"
  • Troubleshooting with libraries: When fixing bugs or errors related to specific libraries

Benefits over WebFetch/WebSearch:

  • Curated, current documentation from official sources
  • Structured format optimized for code generation
  • Topic filtering for focused results
  • Version-specific documentation when needed

Setup

API Key Required: Set CONTEXT7_API_KEY environment variable. Get key from https://context7.com/dashboard

export CONTEXT7_API_KEY="your-api-key"

Quick Start

Two-Step Workflow

  1. Search for library to get Context7-compatible ID
  2. Fetch documentation using that ID

Exception: Skip search if user provides exact ID format (/org/project or /org/project/version)

Searching for Libraries

Use scripts/context7_client.py search to resolve library names to Context7 IDs.

Basic search:

python scripts/context7_client.py search "React"

Output format:

Found 3 results for 'React':

1. React
   ID: /facebook/react
   Description: JavaScript library for building user interfaces

2. React Router
   ID: /remix-run/react-router
   Description: Declarative routing for React

Selection criteria:

  • Exact name matches prioritized
  • Description relevance to query intent
  • Documentation coverage (higher code snippet count)
  • Source reputation (High/Medium preferred)

Common patterns:

# Framework search
python scripts/context7_client.py search "Next.js"
# Returns: /vercel/next.js

# Database client
python scripts/context7_client.py search "MongoDB"
# Returns: /mongodb/docs

# UI library
python scripts/context7_client.py search "shadcn"
# Returns: /shadcn/ui

Fetching Documentation

Use scripts/context7_client.py docs with resolved library ID.

Basic fetch:

python scripts/context7_client.py docs vercel/next.js

With topic filter:

python scripts/context7_client.py docs vercel/next.js --topic routing

With token limit:

python scripts/context7_client.py docs vercel/next.js --tokens 3000

Specific version:

python scripts/context7_client.py docs vercel/next.js/v15.1.8

Combined parameters:

python scripts/context7_client.py docs vercel/next.js --topic "app router" --tokens 2000

Parameters

Library ID Format

  • Standard: /org/project (e.g., /vercel/next.js)
  • Versioned: /org/project/version (e.g., /vercel/next.js/v15.1.8)
  • Leading slash optional: Script handles both vercel/next.js and /vercel/next.js

Optional Filters

  • --topic: Focus on specific subject (e.g., "routing", "hooks", "authentication")
  • --tokens: Limit documentation size (default: 5000)
    • Use lower values (1000-2000) for focused queries
    • Use higher values (5000-10000) for comprehensive references

Output Formats

  • Default: Formatted markdown documentation
  • --json: Raw JSON for programmatic parsing

Error Handling

Common errors:

  1. "Context7 API key required"

    • Set CONTEXT7_API_KEY environment variable
  2. "Authentication failed"

    • Verify API key is correct
    • Check key hasn't been revoked
  3. "Library not found"

    • Verify library ID is correct
    • Try searching first to confirm ID
  4. "Rate limited. Retry after X seconds"

    • Wait specified duration
    • Consider implementing exponential backoff
  5. Network errors

    • Check internet connectivity
    • Verify Context7 API is accessible

Usage Examples

Example 1: Next.js App Router documentation

# Search for Next.js
python scripts/context7_client.py search "Next.js"

# Fetch App Router docs
python scripts/context7_client.py docs vercel/next.js --topic "app router"

Example 2: React hooks with token limit

# Direct fetch (known ID)
python scripts/context7_client.py docs facebook/react --topic hooks --tokens 2000

Example 3: Specific library version

# Search for library
python scripts/context7_client.py search "Tailwind CSS"

# Fetch specific version docs
python scripts/context7_client.py docs tailwindlabs/tailwindcss/v3.4.0

Integration Tips

For code generation

  1. Search for library if ID unknown
  2. Fetch docs with relevant topic filter
  3. Use documentation to generate accurate, up-to-date code
  4. Consider token limits based on scope

For setup/configuration

  1. Fetch docs without topic filter for comprehensive guide
  2. Use higher token limit (5000+) for full instructions
  3. Look for "getting started" or "installation" sections

For API references

  1. Use topic filter for specific API sections
  2. Moderate token limits (2000-3000) for focused references
  3. Fetch multiple topics separately if needed

Token Efficiency

Progressive disclosure vs MCP:

  • MCP: All tools always in context (~2k tokens)
  • This skill:
    • Metadata: ~100 words (always)
    • SKILL.md: <5k words (when triggered)
    • Scripts: Executed without loading to context
    • References: Loaded only when needed

Best practices:

  • Use topic filters to get focused docs
  • Adjust token limits based on query scope
  • Cache results when appropriate
  • Only invoke skill when documentation is actually needed

Resources

scripts/context7_client.py

Python client for Context7 API with CLI interface. Handles authentication, search, and documentation fetching. Can be executed directly without loading to context.

references/api_details.md

Detailed API reference including endpoints, authentication, rate limits, and error codes. Load into context if deeper API understanding is needed for debugging or advanced usage.

Install

Download ZIP
Requires askill CLI v1.0+

AI Quality Score

96/100Analyzed 2/11/2026

An exceptionally well-documented skill for fetching library documentation via the Context7 API. It features clear trigger patterns, detailed CLI examples, comprehensive error handling, and strategic integration tips.

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Metadata

Licenseunknown
Version-
Updated12/16/2025
Publishersyz51

Tags

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