# HumanAIE

> HumanAIE — datboip-humanaie. Use this tool when you need to collaborate with AI agents in a shared browser environment, enabling human-AI interaction to teach and build spatial memory through highlight-to-teach functionality. It solves problems of efficient AI training and knowledge transfer, accepting user highlights as inputs and generating trained AI models as outputs. Ideal for use cases where human expertise needs to be transferred to AI agents, such as data annotation and model training.

Canonical page: https://skillsregistry.net/skills/datboip-humanaie  
JSON: https://api.skillsregistry.net/v1/skills/datboip-humanaie

## Description

Human AI Eyes (pronounced Human-Eye) — shared browser for human-AI collaboration. Highlight-to-teach builds spatial memory for your AI agent.

## Trust

- **Trust score (0–1):** 1.00
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** container
- **Runtime environment:** vm
- **Category:** browser-automation
- **Updated:** 2026-09-27

## Source

- **Source listing:** [GitHub](https://github.com/datboip/HumanAIE)

## 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": "datboip-humanaie"
    }
  }
}
```

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