# agent-memory

> Use this tool when you need to store and retrieve information over time, enabling AI agents to learn from experience and make informed decisions. The agent-memory system solves problems of knowledge retention and recall, allowing agents to adapt to changing environments and improve performance. It accepts input data, stores it in a persistent memory, and outputs retrieved information as needed.

Canonical page: https://skillsregistry.net/skills/dennis-da-menace-agent-memory  
JSON: https://api.skillsregistry.net/v1/skills/dennis-da-menace-agent-memory

## Description

Persistent memory system for AI agents.

## Trust

- **Trust score (0–1):** 0.60
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** instructions
- **Runtime environment:** llm
- **Category:** ai-ml
- **Updated:** 2026-05-15

## Source

- **Source listing:** [ClawHub](https://clawskills.sh/skills/dennis-da-menace-agent-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": "dennis-da-menace-agent-memory"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/dennis-da-menace-agent-memory` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/dennis-da-menace-agent-memory/pull`

---
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
