# handson-coding

> Use this tool when you need to refine AI coding judgment and improve accuracy in evaluating coding practice attempts. It solves problems of inconsistent verdicts by comparing LLM outputs with platform results, allowing for targeted corrections. The tool takes in coding practice attempts and LLM verdicts as inputs, producing refined judgment rules as outputs.

Canonical page: https://skillsregistry.net/skills/jrjuni-handson-mcp  
JSON: https://api.skillsregistry.net/v1/skills/jrjuni-handson-mcp

## Description

Enables recording and analyzing coding practice attempts, comparing LLM verdicts with platform results, and gradually improving LLM judgment through correction rules.

## Trust

- **Trust score (0–1):** 0.69
- **Verification tier:** scanned
- **Last scanned:** 2026-09-03

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-09-03

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/xmgbrrnm55)
- **Repository:** <https://github.com/JrJuni/handson-mcp>

## 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": "jrjuni-handson-mcp"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/jrjuni-handson-mcp` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/jrjuni-handson-mcp/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