# anatid

> anatid — thedatasense-anatid. Use this tool when you need to store and manage local memory for AI agents, tracking evidence, corrections, and history in a single DuckDB file. It solves problems related to data consistency and version control, allowing agents to learn and adapt from their interactions. Ideal for use cases requiring transparent and auditable decision-making processes, with git capabilities for version tracking and collaboration.

Canonical page: https://skillsregistry.net/skills/thedatasense-anatid  
JSON: https://api.skillsregistry.net/v1/skills/thedatasense-anatid

## Description

Local memory for AI agents, with evidence, corrections and history. One DuckDB file.

## Trust

- **Trust score (0–1):** 1.00
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

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

## Source

- **Source listing:** [GitHub](https://github.com/thedatasense/anatid)

## 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": "thedatasense-anatid"
    }
  }
}
```

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