# io.github.JonesRobM/physbound

> Use this tool when you need to validate the physical layer of wireless communication systems, solving problems such as inaccurate RF link budgets, insufficient Shannon capacity, and incorrect noise floor calculations. It takes in link budget parameters and outputs validation results, helping to identify potential issues in wireless system design. Ideal for use in wireless communication system development and optimization contexts.

Canonical page: https://skillsregistry.net/skills/io-github-jonesrobm-physbound  
JSON: https://api.skillsregistry.net/v1/skills/io-github-jonesrobm-physbound

## Description

Physical Layer Linter — validates RF link budgets, Shannon capacity, and noise floors.

## Trust

- **Trust score (0–1):** 0.85
- **Verification tier:** scanned

## Facts

- **Version:** 0.1.1
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** other
- **Updated:** 2026-06-16

## Source

- **Source listing:** [MCP Registry](https://registry.modelcontextprotocol.io/v0/servers/io.github.JonesRobM%2Fphysbound)
- **Repository:** <https://github.com/JonesRobM/physbound>

## 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-jonesrobm-physbound"
    }
  }
}
```

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