# io.github.sunsiyuan/human-survey

> Use this tool when you need to collect feedback from humans to improve AI agent performance, creating customized surveys to gather responses and generate actionable results. It solves problems of AI model evaluation, human-AI interaction assessment, and data collection for machine learning. The tool accepts survey configurations as input and outputs response data and analysis results.

Canonical page: https://skillsregistry.net/skills/io-github-sunsiyuan-human-survey  
JSON: https://api.skillsregistry.net/v1/skills/io-github-sunsiyuan-human-survey

## Description

Feedback collection for AI agents. Create surveys, collect responses, get results.

## Trust

- **Trust score (0–1):** 0.71
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

- **Version:** 0.1.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-09-28

## Source

- **Source listing:** [MCP Registry](https://registry.modelcontextprotocol.io/v0/servers/io.github.sunsiyuan%2Fhuman-survey)
- **Repository:** <https://github.com/sunsiyuan/human-survey>

## 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": "io-github-sunsiyuan-human-survey"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/io-github-sunsiyuan-human-survey` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/io-github-sunsiyuan-human-survey/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