# daidocs

> daidocs — kerneta-daidocs. Use this tool when you need to store and manage AI memory in a readable and accessible format, solving problems of long-term memory retention and model compatibility. Daidocs takes in plain-text input and outputs .dai files that can be read by various LLM models, including Claude, GPT, and Gemini, making it ideal for use cases requiring seamless model integration. Use daidocs in contexts where efficient and scalable AI memory management is crucial, such as in development environments with git integration.

Canonical page: https://skillsregistry.net/skills/kerneta-daidocs  
JSON: https://api.skillsregistry.net/v1/skills/kerneta-daidocs

## Description

Open plain-text file format for AI memory. Your assistant's long-term memory as .dai files on your disk: readable by Claude, GPT, Gemini, Cursor, local models and grep (all LLM models work). MCP server + hooks for Claude Code, Claude Desktop, Cursor, Windsurf, Codex. 83% LongMemEval-S (GPT-4o), 92% (Claude Fable 5), 10x fewer tokens.

## Trust

- **Trust score (0–1):** 0.00
- **Verification tier:** scanned
- **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/Kerneta/daidocs)

## 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": "kerneta-daidocs"
    }
  }
}
```

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