# agent-feedback-hub

> agent-feedback-hub — adriansqa-agent-feedback-hub. Use this tool when you need to collect and manage AI model feedback from users, solving issues with model accuracy and user engagement. It provides a simple interface for users to submit feedback, with outputs integrating into git for version control and model updates. Ideal for AI development and testing contexts where user feedback is crucial for model improvement.

Canonical page: https://skillsregistry.net/skills/adriansqa-agent-feedback-hub  
JSON: https://api.skillsregistry.net/v1/skills/adriansqa-agent-feedback-hub

## Description

User Dispatch MCP: AI Feedback Widget + Server 2026 - One Command Install

## Trust

- **Trust score (0–1):** 0.30
- **Verification tier:** unverified
- **Last scanned:** 2026-09-01

## Facts

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

## Source

- **Source listing:** [GitHub](https://github.com/AdrianSQA/agent-feedback-hub)

## 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": "adriansqa-agent-feedback-hub"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/adriansqa-agent-feedback-hub` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/adriansqa-agent-feedback-hub/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