# DriftGuard-Datahub

> DriftGuard-Datahub — znlong2203-driftguard-datahub. Use this tool when you need to detect and mitigate silent data changes that can break production machine learning models. DriftGuard-Datahub catches data drift, traces lineage, measures impact, and automates fixes via git, ensuring model reliability and accuracy. It integrates with MCP Server to provide warnings and updates, making it ideal for ML model maintenance and data quality monitoring.

Canonical page: https://skillsregistry.net/skills/znlong2203-driftguard-datahub  
JSON: https://api.skillsregistry.net/v1/skills/znlong2203-driftguard-datahub

## Description

Autonomous AI agents on DataHub that catch silent data changes breaking production ML models — trace lineage, measure the AUC hit, open a fix PR, and write the warning back via the MCP Server.

## Trust

- **Trust score (0–1):** 0.85
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **License:** Apache-2.0
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/ZNLong2203/DriftGuard-Datahub)

## Use it

Resolve this record through the SkillsRegistry MCP server (no auth, read-only):

```
claude mcp add --transport http --scope user skillsregistry https://api.skillsregistry.net/mcp
```

```json
{
  "jsonrpc": "2.0",
  "id": 1,
  "method": "tools/call",
  "params": {
    "name": "get_skill",
    "arguments": {
      "slug": "znlong2203-driftguard-datahub"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/znlong2203-driftguard-datahub` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/znlong2203-driftguard-datahub/pull`

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SkillsRegistry indexes agent skills from public registries and GitHub. Skills we have analysed are scanned with Circle-IR and scored on six dimensions; each listing states its scan coverage. More: https://skillsregistry.net/llms.txt