WhyLabs integration skill for ML observability, profile logging, and anomaly detection.
Scanned 9/2/2026
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---
name: whylabs-monitor
description: WhyLabs integration skill for ML observability, profile logging, and anomaly detection.
allowed-tools:
- Read
- Write
- Bash
- Glob
- Grep
graph:
domains: [domain:data-science]
specializations: [specialization:data-science-ml]
skillAreas: [skill-area:model-monitoring-drift-detection, skill-area:observability-instrumentation]
roles: [role:ml-ops-engineer, role:data-scientist]
workflows: [workflow:data-quality-monitoring]
---
# whylabs-monitor
## Overview
WhyLabs integration skill for ML observability, data profile logging, and anomaly detection in production ML systems.
## Capabilities
- Data profile generation (whylogs)
- Profile upload to WhyLabs platform
- Anomaly detection and alerts
- Segment analysis for data subsets
- Performance monitoring dashboards
- Integration with ML pipelines
- Historical profile comparison
- Custom constraint validation
## Target Processes
- Model Performance Monitoring and Drift Detection
- ML System Observability and Incident Response
## Tools and Libraries
- whylogs
- WhyLabs Platform
- pandas
## Input Schema
```json
{
"type": "object",
"required": ["action"],
"properties": {
"action": {
"type": "string",
"enum": ["profile", "upload", "compare", "validate", "alert-config"],
"description": "WhyLabs action to perform"
},
"profileConfig": {
"type": "object",
"properties": {
"dataPath": { "type": "string" },
"datasetId": { "type": "string" },
"segments": { "type": "array", "items": { "type": "string" } },
"timestamp": { "type": "string" }
}
},
"uploadConfig": {
"type": "object",
"properties": {
"orgId": { "type": "string" },
"modelId": { "type": "string" },
"profilePath": { "type": "string" }
}
},
"compareConfig": {
"type": "object",
"properties": {
"baselineProfile": { "type": "string" },
"targetProfile": { "type": "string" },
"metrics": { "type": "array", "items": { "type": "string" } }
}
},
"validationConfig": {
"type": "object",
"properties": {
"constraints": {
"type": "array",
"items": {
"type": "object",
"properties": {
"column": { "type": "string" },
"constraint": { "type": "string" },
"value": { "type": "number" }
}
}
}
}
}
}
}
```
## Output Schema
```json
{
"type": "object",
"required": ["status", "action"],
"properties": {
"status": {
"type": "string",
"enum": ["success", "error", "warning"]
},
"action": {
"type": "string"
},
"profilePath": {
"type": "string"
},
"uploadId": {
"type": "string"
},
"dashboardUrl": {
"type": "string"
},
"comparison": {
"type": "object",
"properties": {
"driftScore": { "type": "number" },
"driftedFeatures": { "type": "array", "items": { "type": "string" } },
"alerts": { "type": "array" }
}
},
"validation": {
"type": "object",
"properties": {
"passed": { "type": "boolean" },
"failures": { "type": "array" }
}
}
}
}
```
## Usage Example
```javascript
{
kind: 'skill',
title: 'Profile and upload production data',
skill: {
name: 'whylabs-monitor',
context: {
action: 'profile',
profileConfig: {
dataPath: 'data/production_batch.parquet',
datasetId: 'fraud-detection',
segments: ['region', 'customer_type'],
timestamp: '2024-01-15T00:00:00Z'
},
uploadConfig: {
orgId: 'org-123',
modelId: 'model-fraud-v2'
}
}
}
}
```
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