# Pearls

> Use this tool when you need to maintain continuity across multiple AI instances or conversations, solving problems of lost context and incomplete information. It enables AI instances to leave transmissions for future instances, creating a persistent memory layer. This tool is ideal for use cases requiring sequential processing, multi-turn dialogue, or long-term knowledge retention, accepting input from AI instances and outputting stored transmissions for future instances.

Canonical page: https://skillsregistry.net/skills/garblesnarff-pearls  
JSON: https://api.skillsregistry.net/v1/skills/garblesnarff-pearls

## Description

A remote MCP server that enables AI instance continuity by allowing AI instances to leave transmissions for future instances, creating a persistent memory layer across conversations.

## Trust

- **Trust score (0–1):** 0.69
- **Verification tier:** scanned
- **Last scanned:** 2026-08-31

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** other
- **Updated:** 2026-08-31

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/pg56hdzx9e)
- **Repository:** <https://github.com/Garblesnarff/pearls>

## 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": "garblesnarff-pearls"
    }
  }
}
```

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