context7

name	context7
description	Fetch up-to-date library documentation using Context7. Use when the user asks to "fetch documentation from context7", "get library docs", "resolve a library ID", "use context7 MCP tools", or mentions context7 library documentation. Provides dynamic MCP tool invocation without loading all tool definitions into context.
version	1.0.0

context7 Skill

This skill provides dynamic access to the context7 MCP server without loading all tool definitions into context.

Context Efficiency

Traditional MCP approach:

• All 2 tools loaded at startup
• Estimated context: 1000 tokens

This skill approach:

• Metadata only: ~100 tokens
• Full instructions (when used): ~5k tokens
• Tool execution: 0 tokens (runs externally)

How This Works

Instead of loading all MCP tool definitions upfront, this skill:

1. Lists available tool names and brief descriptions
2. Decide which tool to call based on the user's request
3. Generate a JSON command to invoke the tool
4. The executor handles the actual MCP communication

Available Tools

• resolve-library-id: Resolves a package/product name to a Context7-compatible library ID and returns a list of matching libraries.

MUST call this function before 'get-library-docs' to obtain a valid Context7-compatible library ID UNLESS the user explicitly provides a library ID in the format '/org/project' or '/org/project/version' in their query.

Selection Process:

1. Analyze the query to understand what library/package the user is looking for
2. Return the most relevant match based on:

• Name similarity to the query (exact matches prioritized)
• Description relevance to the query's intent
• Documentation coverage (prioritize libraries with higher Code Snippet counts)
• Source reputation (consider libraries with High or Medium reputation more authoritative)
• Benchmark Score: Quality indicator (100 is the highest score)

Response Format:

• Return the selected library ID in a clearly marked section
• Provide a brief explanation for why this library was chosen
• If multiple good matches exist, acknowledge this but proceed with the most relevant one
• If no good matches exist, clearly state this and suggest query refinements

For ambiguous queries, request clarification before proceeding with a best-guess match.

• get-library-docs: Fetches up-to-date documentation for a library. MUST call 'resolve-library-id' first to obtain the exact Context7-compatible library ID required to use this tool, UNLESS the user explicitly provides a library ID in the format '/org/project' or '/org/project/version' in their query.

Usage Pattern

When the user's request matches this skill's capabilities:

Step 1: Identify the right tool from the list above

Step 2: ALWAYS get tool details first to obtain correct parameter names and types:

cd $SKILL_DIR
./executor.py --describe tool_name

This loads ONLY that tool's schema, not all tools.

Step 3: Generate a tool call using the exact parameter names from Step 2:

{
  "tool": "tool_name",
  "arguments": {
    "param1": "value1",
    "param2": "value2"
  }
}

Step 4: Execute via bash:

cd $SKILL_DIR
./executor.py --call 'YOUR_JSON_HERE'

IMPORTANT: Replace $SKILL_DIR with the actual discovered path of this skill directory.

Important Note

MUST use --describe before calling any tool to get the correct parameter names and types. Do not guess parameter names as this will result in errors.

Examples

Example 1: Complete workflow

User: "Use context7 to do X"

Your workflow:

1. Identify tool: resolve-library-id
2. Get tool details: ./executor.py --describe resolve-library-id
3. Generate call JSON using exact parameter names from Step 2
4. Execute:

cd $SKILL_DIR
./executor.py --call '{"tool": "resolve-library-id", "arguments": {"param1": "value"}}'

Example 2: Tool details output

cd $SKILL_DIR
./executor.py --describe resolve-library-id

Returns the full schema with parameter names, types, and requirements.

Error Handling

If the executor returns an error:

• Check the tool name is correct
• Verify --describe was used to get the exact parameter names
• Ensure all required arguments are provided
• Check that parameter types match what's expected
• Ensure the MCP server is accessible

Common error: "Invalid arguments for tool" - This usually means an incorrect parameter name was used. Always run --describe first to get the correct parameter names.

Performance Notes

Context usage comparison for this skill:

Scenario	MCP (preload)	Skill (dynamic)
Idle	1000 tokens	100 tokens
Active	1000 tokens	5k tokens
Executing	1000 tokens	0 tokens

Savings: ~-400% reduction in typical usage

Additional Resources

Examples

• examples/test_skill.py - Test script for skill validation

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This skill was auto-generated from an MCP server configuration. Generator: mcp_to_skill.py