shap-explainer

name	shap-explainer
description	SHAP-based model explainability skill for feature attribution, summary plots, and interaction analysis.
allowed-tools	["Read","Write","Bash","Glob","Grep"]

shap-explainer

Overview

SHAP-based model explainability skill for feature attribution, summary plots, interaction analysis, and model interpretation.

Capabilities

• TreeExplainer for tree-based models (XGBoost, LightGBM, Random Forest)
• DeepExplainer for neural networks
• KernelExplainer for model-agnostic explanations
• Summary, dependence, and force plots
• Interaction value computation
• Cohort-based analysis
• Waterfall and bar plots
• Expected value analysis

Target Processes

• Model Interpretability and Explainability Analysis
• Model Evaluation and Validation Framework
• A/B Testing Framework for ML Models

Tools and Libraries

• SHAP
• matplotlib
• numpy

Input Schema

{
  "type": "object",
  "required": ["modelPath", "dataPath", "explainerType"],
  "properties": {
    "modelPath": {
      "type": "string",
      "description": "Path to the trained model"
    },
    "dataPath": {
      "type": "string",
      "description": "Path to data for explanation"
    },
    "explainerType": {
      "type": "string",
      "enum": ["tree", "deep", "kernel", "linear", "gradient"],
      "description": "Type of SHAP explainer to use"
    },
    "analysisConfig": {
      "type": "object",
      "properties": {
        "numSamples": { "type": "integer" },
        "backgroundSamples": { "type": "integer" },
        "featureNames": { "type": "array", "items": { "type": "string" } },
        "outputIndex": { "type": "integer" }
      }
    },
    "plotConfig": {
      "type": "object",
      "properties": {
        "plotTypes": {
          "type": "array",
          "items": { "type": "string", "enum": ["summary", "bar", "waterfall", "force", "dependence", "interaction"] }
        },
        "maxFeatures": { "type": "integer" },
        "outputDir": { "type": "string" }
      }
    }
  }
}

Output Schema

{
  "type": "object",
  "required": ["status", "shapValues"],
  "properties": {
    "status": {
      "type": "string",
      "enum": ["success", "error"]
    },
    "shapValues": {
      "type": "string",
      "description": "Path to SHAP values file"
    },
    "expectedValue": {
      "type": "number"
    },
    "featureImportance": {
      "type": "array"
       
         
         
              
              
              
        
      
    
     
       
       
         
         
              
              
        
      
    
     
       
       
    
  

Usage Example

{
  kind: 'skill',
  title: 'Generate SHAP explanations',
  skill: {
    name: 'shap-explainer',
    context: {
      modelPath: 'models/xgboost_model.pkl',
      dataPath: 'data/test.csv',
      explainerType: 'tree',
      analysisConfig: {
        numSamples: 1000,
        backgroundSamples: 100
      },
      plotConfig: {
        plotTypes: ['summary', 'bar', 'dependence'],
        maxFeatures: 20,
        outputDir: 'explanations/'
      }
    }
  }
}