Generate tailored quality criteria and scoring guides from your task descriptions. Refine objectiv…
Config is the same across clients — only the file and path differ.
{
"mcpServers": {
"ai-smithery-magenie33-quality-dimension-generator": {
"command": "<see-readme>",
"args": []
}
}
}Are you the author?
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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.
No automated test available for this server. Check the GitHub README for setup instructions.
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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.
Install from the Smithery AI Model Context Protocol Registry:
🔗 Get Quality Dimension Generator on Smithery
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.
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
]
}
Contributions welcome! This project is open source under the MIT License.
Transform your work quality today! 🚀