# honeybadger

> honeybadger — kroq86-honeybadger. Use this tool when you need to formally benchmark and inspect the reasoning capabilities of language models on synthetic tasks, solving problems related to machine-like execution semantics and testing their ability to follow precise logical rules. It provides a virtual machine (VM) runtime environment with inspectable outputs, allowing for detailed analysis of language model performance. Ideal for use cases where rigorous testing and evaluation of language models are required, such as in research and development contexts.

Canonical page: https://skillsregistry.net/skills/kroq86-honeybadger  
JSON: https://api.skillsregistry.net/v1/skills/kroq86-honeybadger

## Description

formal VM benchmark and inspectable reasoning runtime for testing whether language models can follow machine-like execution semantics on synthetic tasks.

## Trust

- **Trust score (0–1):** 0.83
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

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

## Source

- **Source listing:** [GitHub](https://github.com/kroq86/honeybadger)

## 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": "kroq86-honeybadger"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/kroq86-honeybadger` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/kroq86-honeybadger/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