MCP For Claude Marketplace
Tool Description Semantic Density Scorer

Tool Description Semantic Density Scorer MCP Connector for Claude

A+

Analyzes LLM tool descriptions to evaluate linguistic precision, verb density, and naming consistency.

3 tools Official Updated Oct 1, 2026 Official Vinkius Partner
More Details Connect to Claude

This MCP server provides advanced linguistic analysis for LLM tool descriptions. It quantifies 'instructional density' by measuring verb density, evaluates parameter naming uniformity (camelCase vs snake_case), and calculates a composite clarity score. Use analyze_description_linguistics to measure action-oriented language, calculate_naming_uniformity to ensure schema consistency, and get_clarity_score to assess overall semantic quality and return-type explicitness.

llmnlptool-callingsemantic-analysisprompt-engineering

3 tools expose this connector's capabilities to your AI agent.

calculate_naming_uniformity

Checks if the parameter naming within the description follows a consistent casing convention

get_clarity_score

Provides a final assessment of how well an LLM will understand the tool based on semantic markers

analyze_description_linguistics

Evaluates the actionable quality of the text by measuring verb density

See how to talk to your AI agent using Tool Description Semantic Density Scorer.

Analyze the verb density of this description: 'This tool is used for fetching user data.'

{"verbCount": 1, "totalWordCount": 10, "densityRatio": 0.1}

Check if the parameter 'user_id' follows camelCase.

{"matchCount": 0, "mismatchCount": 1, "uniformityScore": 0.0}

What is the clarity score for: 'Retrieve user profile by ID. Returns a JSON object.'

{"finalScore": 0.95, "lengthPenalty": 0, "clarityRating": "High"}

Verb density is the ratio of imperative/action verbs to the total word count in a description. High density indicates more direct instructions for the LLM.

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