# Bench

> Use this tool when you need to identify, communicate with, and diagnose USB hardware devices. Bench solves problems related to device recognition, serial communication, and troubleshooting for makers and hardware engineers. It takes input from USB devices and outputs diagnostic information, making it ideal for use cases involving hardware development, testing, and debugging.

Canonical page: https://skillsregistry.net/skills/seayniclabs-bench  
JSON: https://api.skillsregistry.net/v1/skills/seayniclabs-bench

## Description

USB hardware discovery, device identification, serial communication, and diagnostics for makers and hardware engineers.

## Trust

- **Trust score (0–1):** 0.30
- **Verification tier:** unverified
- **Last scanned:** 2026-09-02

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** iot-hardware
- **Updated:** 2026-09-02

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/og001z8ott)
- **Repository:** <https://github.com/seayniclabs/bench>

## 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": "seayniclabs-bench"
    }
  }
}
```

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