# muninn-memory

> Use this tool when you need to enhance an AI agent's ability to store and retrieve information, solving problems related to knowledge retention and recall. The muninn-memory system provides a core functionality of managing data inputs and generating informative outputs, allowing for efficient interface with other AI components. It is ideal for use in contexts where AI agents require persistent memory to learn, adapt, and make informed decisions.

Canonical page: https://skillsregistry.net/skills/phillipneho-muninn-memory  
JSON: https://api.skillsregistry.net/v1/skills/phillipneho-muninn-memory

## Description

Memory system for AI agents.

## Trust

- **Trust score (0–1):** 0.65
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** instructions
- **Runtime environment:** llm
- **Category:** ai-ml
- **Updated:** 2026-05-22

## Source

- **Source listing:** [ClawHub](https://clawskills.sh/skills/phillipneho-muninn-memory)

## 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": "phillipneho-muninn-memory"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/phillipneho-muninn-memory` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/phillipneho-muninn-memory/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
