# guava-memory

> Use this tool when you need to implement a structured episodic memory system that enables efficient storage and retrieval of experiences with associated Q-value scores. It solves problems related to decision-making, learning, and adaptation in complex environments by providing a framework for organizing and evaluating past experiences. The tool takes in experiential data as input and outputs scored memories that can inform future decisions.

Canonical page: https://skillsregistry.net/skills/koatora20-guava-memory  
JSON: https://api.skillsregistry.net/v1/skills/koatora20-guava-memory

## Description

Structured episodic memory with Q-value scoring.

## Trust

- **Trust score (0–1):** 0.30
- **Verification tier:** unverified
- **Last scanned:** 2026-08-23

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** instructions
- **Runtime environment:** llm
- **Category:** other
- **Updated:** 2026-08-23

## Source

- **Source listing:** [ClawHub](https://clawskills.sh/skills/koatora20-guava-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": "koatora20-guava-memory"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/koatora20-guava-memory` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/koatora20-guava-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