# QA Radar

> Use this tool when you need to prioritize file testing for AI agents, as QA Radar provides risk scores based on churn, coverage, and test mapping to optimize testing efficiency. It solves problems of resource-intensive testing and identifies high-risk areas, taking in file data and outputting actionable risk scores. Ideal for use in development and testing contexts where efficient resource allocation is crucial.

Canonical page: https://skillsregistry.net/skills/io-github-muratkus-qaradar  
JSON: https://api.skillsregistry.net/v1/skills/io-github-muratkus-qaradar

## Description

Tells AI agents which files to test first — churn, coverage, and test mapping as risk scores.

## Trust

- **Trust score (0–1):** 0.70
- **Verification tier:** unverified

## Facts

- **Version:** 0.3.5
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-04-25

## Source

- **Source listing:** [MCP Registry](https://registry.modelcontextprotocol.io/v0/servers/io.github.MuratKus%2Fqaradar)
- **Repository:** <https://github.com/Muratkus/qaradar>

## 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-muratkus-qaradar"
    }
  }
}
```

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