# embedded-review

> embedded-review — ylongw-embedded-review. Use this tool when you need to ensure the reliability and security of embedded or firmware code, as it provides a comprehensive review with checklists for memory safety, interrupt handling, and hardware interactions. It solves problems related to code vulnerabilities, memory leaks, and hardware compatibility issues. The tool takes in embedded or firmware code as input and outputs a detailed review report highlighting potential issues and areas for improvement.

Canonical page: https://skillsregistry.net/skills/ylongw-embedded-review  
JSON: https://api.skillsregistry.net/v1/skills/ylongw-embedded-review

## Description

Embedded/firmware code review with memory safety, interrupt, and hardware checklists.

## Trust

- **Trust score (0–1):** 0.30
- **Verification tier:** unverified
- **Last scanned:** 2026-08-23

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** instructions
- **Runtime environment:** llm
- **Category:** iot-hardware
- **Updated:** 2026-09-13

## Source

- **Source listing:** [ClawHub](https://clawskills.sh/skills/ylongw-embedded-review)

## 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": "ylongw-embedded-review"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/ylongw-embedded-review` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/ylongw-embedded-review/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