# peak-performance

> peak-performance — frankxai-peak-performance. Use this tool when you need to assess and optimize the performance of AI-powered development machines, solving issues related to system health and creative capacity. It takes machine metrics as input and outputs a Ten Gate score, providing a comprehensive evaluation of system performance. Utilize peak-performance in development environments where maximizing creative output and efficiency is crucial, via its CLI, MCP server, or Claude Code plugin interface.

Canonical page: https://skillsregistry.net/skills/frankxai-peak-performance  
JSON: https://api.skillsregistry.net/v1/skills/frankxai-peak-performance

## Description

System health auditor for AI-powered development machines. Ten Gate scoring maps machine metrics to creative capacity. CLI + MCP server + Claude Code plugin. By Arcanea.

## Trust

- **Trust score (0–1):** 0.84
- **Verification tier:** verified
- **Last scanned:** 2026-09-28

## Facts

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

## Source

- **Source listing:** [GitHub](https://github.com/frankxai/peak-performance)

## 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": "frankxai-peak-performance"
    }
  }
}
```

REST: `GET https://api.skillsregistry.net/v1/skills/frankxai-peak-performance` · pull for local use: `GET https://api.skillsregistry.net/v1/skills/frankxai-peak-performance/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