# ERINYS-mem

> ERINYS-mem — ghostyai-ha-erinys-mem. Use this tool when you need to optimize AI agent performance by managing memory and refining knowledge retention. ERINYS-mem solves problems related to information overload and inefficient learning by forgetting irrelevant data, distilling key insights, and generating new ideas. It accepts inputs from various sources, outputs refined memory structures, and is ideal for use in complex, dynamic environments where adaptability is crucial.

Canonical page: https://skillsregistry.net/skills/ghostyai-ha-erinys-mem  
JSON: https://api.skillsregistry.net/v1/skills/ghostyai-ha-erinys-mem

## Description

Reflexive memory for AI agents — forgets, distills, and dreams. MCP server with 28 tools.

## Trust

- **Trust score (0–1):** 0.50
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Category:** ai-ml
- **Updated:** 2026-09-21

## Source

- **Source listing:** [GitHub](https://github.com/GhostyAI-HA/ERINYS-mem)

## 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": "ghostyai-ha-erinys-mem"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/ghostyai-ha-erinys-mem` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/ghostyai-ha-erinys-mem/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