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MCP server · Productivity

ai.smithery/magenie33-quality-dimension-generator

Generate tailored quality criteria and scoring guides from your task descriptions. Refine objectiv…

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Scored 6 months ago · breakdown

About ai.smithery/magenie33-quality-dimension-generator

ai.smithery/magenie33-quality-dimension-generator is an MCP server in the Productivity category: generate tailored quality criteria and scoring guides from your task descriptions. Refine objectiv….

Install

From source
git clone https://github.com/magenie33/quality-dimension-generator

This server has no ConduID identity, so agent calls to it are not receipted. Pin the version you install and review the source before granting it credentials.

Tools (2)

generate_quality_dimensions_promptGenerate quality dimensions prompt based on task analysis. Uses default target score from configuration or task complexity to determine evaluation strictness.

Parameters not published.

generate_task_analysis_promptGenerate task analysis prompt for LLM to analyze core tasks in user conversations

Parameters not published.

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README

Quality Dimension Generator

TypeScript MCP

An MCP server that generates quality evaluation standards for any task. Transform vague requirements into precise, measurable quality criteria with AI-powered analysis, ultimately improving your final work quality.

🎯 What It Does

  • 📊 Analyzes your tasks - Understand what needs to be accomplished
  • 🎯 Creates evaluation standards - Generate specific quality dimensions with scoring criteria
  • 📈 Sets target scores - Define expected quality levels (e.g., 8/10)
  • ✅ Guides execution - Help you complete tasks with clear quality standards

🚀 Quick Start

Installation

Install from the Smithery AI Model Context Protocol Registry:

🔗 Get Quality Dimension Generator on Smithery

Basic Usage

Step 1: Generate task analysis

generate_task_analysis_prompt({
  userMessage: "Write a 1000-word article about AI"
})

Step 2: Generate quality standards

generate_quality_dimensions_prompt({
  taskAnalysisJson: "..." // JSON from step 1
})

Result: Get comprehensive quality evaluation criteria with target scores, then complete your task following those standards.

📋 Example Output

For the task "Write a technical blog post":

{
  "expectedScore": 8,
  "scoreCalculation": "Average of all 5 dimension scores",
  "dimensions": [
    {
      "name": "Technical Accuracy",
      "description": "Correctness and depth of technical content",
      "importance": "Ensures readers get reliable information",
      "scoring": {
        "10": "All technical details verified and comprehensive",
        "8": "Mostly accurate with minor gaps",
        "6": "Generally correct but lacks depth"
      }
    }
    // ... 4 more dimensions
  ]
}

💡 Use Cases

  • Software Development - Code quality, testing, documentation standards
  • Content Creation - Writing quality, SEO, engagement metrics
  • Project Management - Deliverable criteria, timeline adherence
  • Research - Methodology, accuracy, presentation standards

🤝 Contributing

Contributions welcome! This project is open source under the MIT License.

🔗 Resources


Transform your work quality today! 🚀

README copy captured when this server was indexed; it may lag the repository. The original is authoritative.

Questions

About ai.smithery/magenie33-quality-dimension-generator

How do I install ai.smithery/magenie33-quality-dimension-generator?

No package has been published for this server, so install it from source: clone the repository and follow its README.

Is ai.smithery/magenie33-quality-dimension-generator safe to use with an AI agent?

Its trust score is 34 out of 100 (low). It passes 1 of the 1 static security checks run so far. It has no ConduID identity yet, so agent calls to it are not receipted.

Is ai.smithery/magenie33-quality-dimension-generator still maintained?

Conduid hasn't recorded a commit date for this repository yet. Check the repository directly for recent activity.