# io.github.LanceRoylo/mcp

> Use this tool when you need to evaluate and optimize AI agent performance, particularly for AEO scoring, auditing llms.txt files, and assessing agent readiness. It solves problems related to AI agent evaluation, auditing, and optimization, providing valuable insights for improvement. The tool takes in relevant AI agent data as input and outputs scores, audit results, and readiness checks, helping users refine their AI agents in various contexts.

Canonical page: https://skillsregistry.net/skills/io-github-lanceroylo-mcp  
JSON: https://api.skillsregistry.net/v1/skills/io-github-lanceroylo-mcp

## Description

AEO scoring, llms.txt audit, and agent-readiness checks for AI agents.

## Trust

- **Trust score (0–1):** 0.97
- **Verification tier:** verified
- **Last scanned:** 2026-09-19

## Facts

- **Version:** 0.1.1
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-09-19

## Source

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

## 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-lanceroylo-mcp"
    }
  }
}
```

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