Tool Definition Quality Score (TDQS)

Overview

An open framework that scores how well an MCP tool definition communicates to an AI agent. It provides a standardized way to evaluate the clarity and completeness of tool descriptions and parameters.

Best for

Best for
Developers building or maintaining MCP tools for AI agent consumption

Use cases

• Assessing MCP tool definitions for AI agent readiness
• Improving documentation quality for tool-consuming agents
• Establishing a baseline for tool definition consistency

Notes

An open framework that scores how well an MCP tool definition communicates to an AI agent. It provides a standardized way to evaluate the clarity and completeness of tool descriptions and parameters.

5 stars on GitHub. Last updated 2026-06-15.

Use cases

• Assessing MCP tool definitions for AI agent readiness
• Improving documentation quality for tool-consuming agents
• Establishing a baseline for tool definition consistency

Pros

• Open source and freely available
• Offers a clear, measurable scoring approach
• Helps identify gaps in tool definitions

Cons

• Requires integration into existing workflows
• Scoring criteria may be subjective in practice
• Limited community adoption reduces comparative benchmarks

Indexed from awesome-mcp-servers-punkpeye and enriched against its public facts.