# sq-memory

> sq-memory — wbic16-sq-memory. Use this tool when you need to enable persistent memory for OpenClaw agents, allowing them to retain information and learn from past interactions. It solves the problem of agent memory loss, enabling more effective and personalized interactions over time. The sq-memory tool takes agent data as input and provides a persistent memory output, ideal for use cases requiring long-term agent knowledge retention.

Canonical page: https://skillsregistry.net/skills/wbic16-sq-memory  
JSON: https://api.skillsregistry.net/v1/skills/wbic16-sq-memory

## Description

**Give your OpenClaw agents permanent memory.**.

## Trust

- **Trust score (0–1):** 0.65
- **Verification tier:** scanned
- **Last scanned:** 2026-05-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** instructions
- **Runtime environment:** llm
- **Category:** other
- **Updated:** 2026-09-24

## Source

- **Source listing:** [ClawHub](https://clawskills.sh/skills/wbic16-sq-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": "wbic16-sq-memory"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/wbic16-sq-memory` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/wbic16-sq-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