# twinify

> Use this tool when you need to create realistic AI digital twins of individuals based on their WhatsApp chat history. Twinify solves the problem of generating accurate and personalized AI models by leveraging chat exports as input, producing digital twins that can simulate human-like conversations. It takes WhatsApp chat history exports as input and outputs a unique AI digital twin, ideal for use cases like chatbots, virtual assistants, or social simulations.

Canonical page: https://skillsregistry.net/skills/neobotjan2026-twinify  
JSON: https://api.skillsregistry.net/v1/skills/neobotjan2026-twinify

## Description

Create AI digital twins of real people from WhatsApp chat history exports.

## Trust

- **Trust score (0–1):** 0.60
- **Verification tier:** unverified

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** instructions
- **Runtime environment:** llm
- **Category:** communication
- **Updated:** 2026-04-22

## Source

- **Source listing:** [ClawHub](https://clawskills.sh/skills/neobotjan2026-twinify)

## 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": "neobotjan2026-twinify"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/neobotjan2026-twinify` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/neobotjan2026-twinify/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