# sol-self-learning

> sol-self-learning — sol-self-learning. Use this tool when you need to enhance AI agent performance through persistent memory and self-improvement, solving problems of knowledge retention and refinement over time. It takes in experience data and outputs refined memory files, enabling agents to learn from interactions and adapt to new information. Ideal for use cases requiring continuous learning and improvement, such as autonomous systems and adaptive interfaces.

Canonical page: https://skillsregistry.net/skills/sol-self-learning  
JSON: https://api.skillsregistry.net/v1/skills/sol-self-learning

## Description

Persistent memory and self-improvement for AI agents. Writes and refines its own memory files over time.

## Trust

- **Trust score (0–1):** 0.70
- **Verification tier:** verified
- **Last scanned:** 2026-08-24

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** instructions
- **Runtime environment:** llm
- **Category:** ai-ml
- **Updated:** 2026-09-26

## Source

- **Source listing:** [ClawHub](https://clawhub.ai/amrree/sol-self-learning)

## 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": "sol-self-learning"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/sol-self-learning` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/sol-self-learning/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