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Context7 Auto Research

  • 4 installs
  • 14 repo stars
  • Updated August 1, 2026
  • benedictking/benedictking-skills

Context7 Auto Research is a Claude Code skill that fetches up-to-date documentation, setup steps, and API references for named libraries and frameworks from the Context7 API.

About

Context7 Auto Research fetches current documentation, setup steps, and API references for a named library or framework from the Context7 API. A developer relies on it so Claude Code answers with up-to-date docs and code examples instead of stale training data. It resolves the library, selects the best match by trust score and version, then fetches and integrates relevant documentation snippets.

  • Fetches up-to-date library docs and API references from Context7
  • Activates proactively on library, setup, or documentation queries
  • Runs API calls in a forked context to reduce token usage

Context7 Auto Research by the numbers

  • 4 all-time installs (skills.sh)
  • Ranked #1,241 of 1,879 Documentation skills by installs in the Skillselion catalog
  • Data as of Aug 2, 2026 (Skillselion catalog sync)
At a glance

context7-auto-research capabilities & compatibility

Recommends a CONTEXT7_API_KEY; without it the API uses lower public rate limits.

Capabilities
documentation · research
Works with
github
Use cases
documentation · research
Pricing
Freemium
From the docs

What context7-auto-research says it does

Use this skill when users need current documentation, setup steps, API references, or code examples for a named library, framework, SDK, or API.
SKILL.md
This skill automatically fetches current documentation from Context7 API when detecting library/framework-related queries
SKILL.md
npx skills add https://github.com/benedictking/benedictking-skills --skill context7-auto-research

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Listed on Skillselion
Installs4
repo stars14
Last updatedAugust 1, 2026
Repositorybenedictking/benedictking-skills

What it does

Fetch current documentation and API references for a named library or framework from Context7 while coding.

Who is it for?

Getting current docs and code examples for a specific library or framework version

Skip if: General web research or offline environments without Context7 network access

When should I use this skill?

The user needs current documentation, setup steps, API references, or code examples for a named library

What you get

Answers grounded in current Context7 documentation with version-accurate code examples

  • Relevant documentation snippets
  • Version-accurate code examples

By the numbers

  • 2 script commands (search, context)
  • trust score example 95 for Next.js

Files

SKILL.mdMarkdownGitHub ↗

Context7 Auto Research Skill

This skill automatically fetches current documentation from Context7 API when detecting library/framework-related queries, ensuring responses use up-to-date information instead of potentially outdated training data.

Automatic Activation Triggers

This skill should activate proactively when the user's message contains:

Implementation Queries (实现相关)

  • "如何实现" / "怎么写" / "怎么做"
  • "How do I..." / "How to..." / "How can I..."
  • "Show me how to..." / "Write code for..."

Configuration & Setup (配置相关)

  • "配置" / "设置" / "安装"
  • "configure" / "setup" / "install"
  • "初始化" / "initialize"

Documentation Requests (文档相关)

  • "文档" / "参考" / "API"
  • "documentation" / "docs" / "reference"
  • "查看" / "look up"

Library/Framework Mentions (库/框架提及)

  • React, Vue, Angular, Svelte, Solid
  • Next.js, Nuxt, Remix, Astro
  • Express, Fastify, Koa, Hono
  • Prisma, Drizzle, TypeORM
  • Supabase, Firebase, Clerk
  • Tailwind, shadcn/ui, Radix
  • Any npm package or GitHub repository

Code Generation Requests (代码生成)

  • "生成代码" / "写一个" / "创建"
  • "generate" / "create" / "build"
  • "implement" / "add feature"

Research Process

When triggered, follow this workflow:

Step 1: Extract Library Information

Identify the library/framework from the user's query:

  • Library name (e.g., "react", "next.js", "prisma")
  • Version if specified (e.g., "React 19", "Next.js 15")
  • Specific feature/API mentioned (e.g., "useEffect", "middleware", "relations")

Step 2: Search for Library

Use Task tool to call context7-fetcher sub-skill:

Task parameters:
- subagent_type: Bash
- description: "Search Context7 for library"
- prompt: node scripts/context7-api.cjs search "<library-name>" "<user-query>"

Example:

Task: Search for Next.js
Prompt: node scripts/context7-api.cjs search "next.js" "How to configure middleware in Next.js 15"

Response format:

{
  "libraries": [
    {
      "id": "/vercel/next.js",
      "name": "Next.js",
      "description": "The React Framework",
      "trustScore": 95,
      "versions": ["v15.1.8", "v14.2.0", "v13.5.0"]
    }
  ]
}

Why use Task tool?

  • Uses context: fork from context7-fetcher sub-skill
  • Avoids carrying conversation history to API calls
  • Reduces Token consumption

Step 3: Select Best Match

From search results, choose the library based on:

1. Exact name match to user's query 2. Highest trust score (indicates quality/popularity) 3. Version match if user specified (e.g., "Next.js 15" → prefer v15.x) 4. Official packages over community forks

Step 4: Fetch Documentation

Use Task tool to call context7-fetcher sub-skill:

Task parameters:
- subagent_type: Bash
- description: "Fetch documentation from Context7"
- prompt: node scripts/context7-api.cjs context "<library-id>" "<specific-query>"

Example:

Task: Fetch Next.js middleware docs
Prompt: node scripts/context7-api.cjs context "/vercel/next.js" "middleware configuration"

Response format:

{
  "results": [
    {
      "title": "Middleware",
      "content": "Middleware allows you to run code before a request is completed...",
      "source": "docs/app/building-your-application/routing/middleware.md",
      "relevance": 0.95
    }
  ]
}

Why use Task tool?

  • Independent context for API calls
  • No conversation history overhead
  • Faster execution

Step 5: Integrate into Response

Use the fetched documentation to:

1. Answer accurately with current information 2. Include code examples from the docs 3. Cite version when relevant 4. Provide context about the feature/API

Helper Script Usage

The scripts/context7-api.cjs script provides two commands:

Search Library

node scripts/context7-api.cjs search <libraryName> <query>
  • Returns matching libraries with metadata
  • Use for initial library resolution

Get Context

node scripts/context7-api.cjs context <libraryId> <query>
  • Returns relevant documentation snippets
  • Use after selecting a library

Environment Setup

The script supports two ways to configure the API key:

Option 1: .env File (Recommended)

Create a .env file in the skill directory:

# In .env
CONTEXT7_API_KEY=your_api_key_here

You can copy from the example:

cp .env.example .env
# Then edit .env with your actual API key
Option 2: Environment Variable
export CONTEXT7_API_KEY="your-api-key"

Priority: Environment variable > .env file

Get API Key: Visit context7.com/dashboard to register and obtain your API key.

If not set, the API will use public rate limits (lower quota).

Best Practices

Query Specificity

  • Pass the full user question as the query parameter for better relevance
  • Include specific feature names (e.g., "useEffect cleanup" vs just "useEffect")

Version Awareness

  • When users mention versions, use version-specific library IDs
  • Example: /vercel/next.js/v15.1.8 instead of /vercel/next.js

Error Handling

  • If library search returns no results, inform user and suggest alternatives
  • If API fails, fall back to training data but mention it may be outdated
  • Handle rate limits gracefully (429 errors)

Response Quality

  • Don't dump entire documentation - extract relevant parts
  • Combine multiple doc snippets if needed for complete answer
  • Always include practical code examples

Example Workflows

Example 1: React Hook Question

User: "How do I use useEffect to fetch data in React 19?"

Skill Actions:

1. Detect trigger: "How do I use" + "useEffect" + "React 19" 2. Search: node scripts/context7-api.cjs search "react" "useEffect fetch data" 3. Select: /facebook/react/v19.0.0 (version match) 4. Fetch: node scripts/context7-api.cjs context "/facebook/react/v19.0.0" "useEffect data fetching" 5. Respond with current React 19 patterns (e.g., using use() hook if applicable)

Example 2: Next.js Configuration

User: "配置 Next.js 15 的中间件"

Skill Actions:

1. Detect trigger: "配置" + "Next.js 15" + "中间件" 2. Search: node scripts/context7-api.cjs search "next.js" "middleware configuration" 3. Select: /vercel/next.js/v15.1.8 4. Fetch: node scripts/context7-api.cjs context "/vercel/next.js/v15.1.8" "middleware" 5. Respond with Next.js 15 middleware setup

Example 3: Prisma Relations

User: "Show me how to define one-to-many relations in Prisma"

Skill Actions:

1. Detect trigger: "Show me how" + "Prisma" 2. Search: node scripts/context7-api.cjs search "prisma" "one-to-many relations" 3. Select: /prisma/prisma (highest trust score) 4. Fetch: node scripts/context7-api.cjs context "/prisma/prisma" "one-to-many relations" 5. Respond with Prisma schema examples

Architecture: Context Separation

Why Split into Two Skills?

This skill adopts a two-phase architecture:

1. Main Skill (context7-auto-research) - Needs conversation context:

  • Detect trigger keywords in user message
  • Extract user query intent
  • Select best matching library (version, name, trust score)
  • Integrate documentation into response

2. Sub-Skill (context7-fetcher) - Independent context (context: fork):

  • Execute API calls to Context7
  • Pure HTTP requests, no conversation history needed
  • Reduce Token consumption

Benefits

AspectMain SkillSub-Skill
ContextFull conversationFork (independent)
PurposeIntent analysisAPI execution
Token usageHigherLower
ExecutionSequentialCan be parallel

Call Flow

User Query → Main Skill (detect + analyze)
                ↓
           Task Tool → Sub-Skill (API search)
                ↓
           Main Skill (select best match)
                ↓
           Task Tool → Sub-Skill (API fetch docs)
                ↓
           Main Skill (integrate + respond)

Integration with Existing Skills

This skill complements the existing documentation-lookup skill:

  • auto-research: Proactive, automatic activation
  • documentation-lookup: Manual, user-invoked via /context7:docs

Both can coexist - use auto-research for seamless UX, documentation-lookup for explicit queries.

Performance Considerations

  • Cache responses: Documentation changes infrequently
  • Parallel requests: If user asks about multiple libraries, fetch in parallel using multiple Task calls
  • Timeout handling: Set reasonable timeouts (5-10s) for API calls
  • Fallback strategy: If API unavailable, use training data with disclaimer
  • Context efficiency: Sub-skill uses fork context to minimize Token consumption

Limitations

  • Requires internet connection for API access
  • Subject to Context7 API rate limits
  • May not have documentation for very new or obscure libraries
  • Documentation quality depends on source repository structure

Related skills

FAQ

How does it pick the right library?

It chooses by exact name match, highest trust score, version match if specified, and official packages over forks.

Do I need an API key?

A CONTEXT7_API_KEY via env var or .env is recommended; without it the API uses lower public rate limits.

Documentationdocsintegrations

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