# intero

> intero — tongriyaotxt-intero. Use this tool when you need to enhance frozen large language models (LLMs) with memory and heartbeat capabilities, allowing them to recall user interactions and initiate conversations. It solves problems of static model responses and enables more dynamic user engagement. With git integration, intero takes in frozen LLMs and outputs interactive, memory-equipped models.

Canonical page: https://skillsregistry.net/skills/tongriyaotxt-intero  
JSON: https://api.skillsregistry.net/v1/skills/tongriyaotxt-intero

## Description

A memory & heartbeat organ for frozen LLMs — it remembers you, and speaks first | 给冻结大模型外挂记忆与心跳器官

## Trust

- **Trust score (0–1):** 0.72
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Updated:** 2026-09-28

## Source

- **Source listing:** [GitHub](https://github.com/tongriyaotxt/intero)

## 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": "tongriyaotxt-intero"
    }
  }
}
```

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