model-card-generator

name	model-card-generator
description	Model documentation skill for generating model cards following Google's model card framework.
allowed-tools	["Read","Write","Bash","Glob","Grep"]
graph	{"domains":["domain:data-science"],"specializations":["specialization:data-science-ml"],"skillAreas":["skill-area:ml-governance-compliance","skill-area:explainability-interpretation"],"roles":["role:data-scientist","role:ml-ops-engineer"],"workflows":["workflow:ml-model-lifecycle"]}

model-card-generator

Overview

Model documentation skill for generating comprehensive model cards following Google's model card framework for ML model documentation.

Capabilities

• Model details documentation (architecture, training, etc.)
• Intended use specification
• Performance metrics documentation
• Ethical considerations section
• Caveats and limitations
• Quantitative analysis sections
• Version history tracking
• Multiple output formats (HTML, Markdown, JSON)

Target Processes

• Model Interpretability and Explainability Analysis
• Model Evaluation and Validation Framework
• ML Model Retraining Pipeline

Tools and Libraries

• Model Card Toolkit
• TensorFlow Model Analysis (optional)
• Jinja2 (templating)

Input Schema

{
  "type": "object",
  "required": ["modelDetails", "intendedUse"],
  "properties": {
    "modelDetails": {
      "type": "object",
      "properties": {
        "name": { "type": "string" },
        "version": { "type": "string" },
        "type": { "type": "string" },
        "architecture": { "type": "string" },
        "trainingDate": { "type": "string" },
        "framework": { "type": "string" },
        "citations": { "type": "array", "items": { "type": "string" } },
        "license": { "type": "string" }
      }
    },
    "intendedUse": {
      "type": "object",
      "properties": {
        "primaryUses": { "type": "array", "items": { "type": "string" } },
        "primaryUsers": { "type": "array", "items": { "type": "string" } },
        "outOfScopeUses": { "type": "array", "items": { "type": "string" } }
      }
    },
    "factors": {
      "type": "object",
      "properties": {
        "relevantFactors": { "type": "array", "items": { "type": "string" } },
        "evaluationFactors": { "type": "array", "items": { "type": "string" } }
      }
    },
    "metrics": {
      "type": "object",
      "properties": {
        "performanceMetrics": { "type": "array" },
        "decisionThresholds": { "type": "object" },
        "variationApproaches": { "type": "array" }
      }
    },
    "evaluationData": {
      "type": "object",
      "properties": {
        "datasets": { "type": "array" },
        "motivation": { "type": "string" },
        "preprocessing": { "type": "string" }
      }
    },
    "trainingData": {
      "type": "object",
      "properties": {
        "datasets": { "type": "array" },
        "motivation": { "type": "string" },
        "preprocessing": { "type": "string" }
      }
    },
    "ethicalConsiderations": {
      "type": "array",
      "items": {
        "type": "object",
        "properties": {
          "name": { "type": "string" },
          "mitigationStrategy": { "type": "string" }
        }
      }
    },
    "caveatsAndRecommendations": {
      "type": "array",
      "items": { "type": "string" }
    },
    "outputConfig": {
      "type": "object",
      "properties": {
        "format": { "type": "string", "enum": ["html", "markdown", "json"] },
        "outputPath": { "type": "string" }
      }
    }
  }
}

Output Schema

{
  "type": "object",
  "required": ["status", "modelCardPath"],
  "properties": {
    "status": {
      "type": "string",
      "enum": ["success", "error"]
    },
    "modelCardPath": {
      "type": "string"
    },
    "format": {
      "type": "string"
    },
    "sections": {
      "type": "array",
      "items": {   
    
     
       
          
       
    
  

Usage Example

{
  kind: 'skill',
  title: 'Generate model card',
  skill: {
    name: 'model-card-generator',
    context: {
      modelDetails: {
        name: 'Fraud Detection Model',
        version: '2.0.0',
        type: 'Binary Classification',
        architecture: 'XGBoost',
        trainingDate: '2024-01-15',
        framework: 'scikit-learn',
        license: 'Proprietary'
      },
      intendedUse: {
        primaryUses: ['Transaction fraud detection'],
        primaryUsers: ['Risk management team'],
        outOfScopeUses: ['Credit scoring', 'Identity verification']
      },
      metrics: {
        performanceMetrics: [
          { name: 'AUC-ROC', value: 0.95 },
          { name: 'Precision@0.5', value: 0.87 }
        ]
      },
      ethicalConsiderations: [
        { name: 'Demographic bias', mitigationStrategy: 'Regular fairness audits' }
      ],
      outputConfig: {
        format: 'markdown',
        : 
      }
    }
  }
}