# drift

> drift — lungenemptynester200-drift. Use this tool when you need to detect changes in your AI-assisted codebase's architecture, solving issues of unintended model updates and integration errors. It analyzes git repositories to identify drift through deterministic checks, providing clear signals for corrective action. Ideal for maintaining model consistency and reliability in machine learning projects.

Canonical page: https://skillsregistry.net/skills/lungenemptynester200-drift  
JSON: https://api.skillsregistry.net/v1/skills/lungenemptynester200-drift

## Description

Detect architecture drift in AI-assisted codebases with deterministic checks and clear signals

## Trust

- **Trust score (0–1):** 0.96
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Category:** other
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/lungenemptynester200/drift)

## 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": "lungenemptynester200-drift"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/lungenemptynester200-drift` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/lungenemptynester200-drift/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