# fsxmemory

> Use this tool when you need to manage and organize complex data structures for AI agents, solving problems of data fragmentation and inefficient memory allocation. The fsxmemory system provides a structured approach to memory management, accepting inputs of varied data types and outputs of organized, easily accessible information. Ideal for use in applications requiring efficient data retrieval and storage, such as knowledge graphs, expert systems, and machine learning models.

Canonical page: https://skillsregistry.net/skills/azrijamil-fsxmemory  
JSON: https://api.skillsregistry.net/v1/skills/azrijamil-fsxmemory

## Description

Structured memory system for AI agents.

## Trust

- **Trust score (0–1):** 0.65
- **Verification tier:** scanned
- **Last scanned:** 2026-05-21

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** instructions
- **Runtime environment:** llm
- **Category:** ai-ml
- **Updated:** 2026-05-21

## Source

- **Source listing:** [ClawHub](https://clawskills.sh/skills/azrijamil-fsxmemory)

## 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": "azrijamil-fsxmemory"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/azrijamil-fsxmemory` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/azrijamil-fsxmemory/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