Magenie33 Quality Dimension Generator

ai.smitheryPublished by smithery.aiOfficial publisherv1.0.0Updated Oct 24, 2026

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

The publisher's own server: 222wcnm Bilistalkermcp

VerifiedStreamable HTTPWeb executableAI & ML

Overview

AI-generated overview

Generates tailored quality criteria and scoring guides from task descriptions, turning vague requirements into measurable quality standards for an assistant.

What you can do
Analyze a task description to identify what needs to be accomplished. Generate specific quality dimensions with scoring criteria and a target score. Run a two-step flow: first a task analysis prompt, then quality standards from that analysis. Use the output as a rubric while completing the task.
When to use it
Use it when you have a vague task and want concrete, measurable quality criteria and a target score before doing and checking the work. Fits writing, code, project deliverables or research where a scoring rubric helps.
Requirements
Needs a remote endpoint connection and a Smithery bearer token supplied in the Authorization header. No local package or environment variables required.
Before you install
Requires a Smithery authentication token in the Authorization header; keep it private. Task descriptions are sent to a remote service, so avoid including confidential or sensitive content. The tools produce prompts and criteria rather than changing data directly.

Installation

In SourceWeft

  1. Open Magenie33 Quality Dimension Generator in the dashboard and add it to a workspace.
  2. Connect Authorization token credentials. They are stored privately and never shown on public pages.
  3. Enable the server for the chats that should use its tools.

Web executable via Streamable HTTP. Remote servers run from the web runtime once configured in a workspace.

Use with an agent

Paste this prompt into Claude Code, Codex, Cursor or another agent — or into SourceWeft chat. The agent reads this server's install guide, shows you its publisher, endpoint and sign-in, and adds it to your client once you agree. Keys never go into a command.

Read https://sourceweft.com/mcp/ai.smithery%2Fmagenie33-quality-dimension-generator/install.md and connect the MCP server it describes to my client. Before changing any config, show me its publisher, endpoint and sign-in method and wait for my OK. Never put an API key in a command or in a file I would commit; ask me where it should come from.

Read the install guide the agent follows

Other MCP clients

Add this to your client's mcpServers config.

{
  "mcpServers": {
    "magenie33-quality-dimension-generator": {
      "type": "http",
      "url": "https://server.smithery.ai/@magenie33/quality-dimension-generator/mcp",
      "headers": {
        "Authorization": "Bearer <YOUR_TOKEN>"
      }
    }
  }
}

README

Quality Dimension Generator

[License: MIT] [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

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

Step 2: Generate quality standards

javascript
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":

json
{  "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! 🚀

Source: README.md at commit c2943f0

Tools

0
SourceWeft has not read this server's tools yet.

Version history

1
  1. v1.0.0LatestSep 16, 2026

Score

75% of the applicable checks met

How complete this listing is, computed from the registry entry, the endpoint and public sources. Not a rating of the server and not a statement that it is safe or working today: reachability is a dated check, and no installs or reviews go into the score.

  • Reached in the last 30 daysRequired25 pts
  • Auth declaredRequired10 pts
  • Tools listedRequired15 pts

    Answer tools/list without a credential, or ship a package that starts in a sandbox without one.

  • DescriptionRequired15 pts
  • Logo10 pts
  • Documentation15 pts
  • License10 pts

    Declare a license in the repository or the registry entry.

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