ai.smithery/magenie33-quality-dimension-generator
Generate tailored quality criteria and scoring guides from your task descriptions. Refine objectiv…
Open source Repository Open in the app JSON README (API)
About
Generate tailored quality criteria and scoring guides from your task descriptions. Refine objectiv…
Details
- Kind
- MCP servers
- Topic
- No topic detected
- Publisher
- ai.smithery
- Origin
- official
- Category
- ferramentas
- Transport
- http
- Version
- 1.0.0
- Last push
- 2025-09-22T09:26:44Z
- Repository state
- ativo
- Language
- JavaScript
- Added
- 2026-08-29 03:00:39
- Updated
- 2026-08-29 03:00:39
- Origin id
ai.smithery/magenie33-quality-dimension-generator
README
# Quality Dimension Generator
[](https://opensource.org/licenses/MIT)
[](https://www.typescriptlang.org/)
[](https://modelcontextprotocol.io/)
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](https://smithery.ai/server/@magenie33/quality-dimension-generator)**
### 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
- [Model Context Protocol Documentation](https://modelcontextprotocol.io/docs)
- [Smithery MCP Registry](https://smithery.ai/)
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**Transform your work quality today!** 🚀