# XFMS

> XFMS — visionairyse-xfms. Use this tool when you need to select the best Large Language Model (LLM) for a specific task, as it aggregates benchmark data and user intent to provide a ranked shortlist with clear explanations. It solves the problem of LLM selection by considering various factors and user requirements, saving time and effort. The tool takes in user intent and task specifications as input and returns a shortlist of optimal LLMs with plain-English rationale as output.

Canonical page: https://skillsregistry.net/skills/visionairyse-xfms  
JSON: https://api.skillsregistry.net/v1/skills/visionairyse-xfms

## Description

Enables users to select the optimal LLM for their specific task by aggregating benchmark data and user intent, returning a ranked shortlist with plain-English rationale.

## Trust

- **Trust score (0–1):** 0.69
- **Verification tier:** scanned
- **Last scanned:** 2026-09-03

## Facts

- **Version:** 1.0.0
- **Skill type:** atomic
- **Execution layer:** mcp-remote
- **Runtime environment:** api
- **Category:** ai-ml
- **Updated:** 2026-09-03

## Source

- **Source listing:** [Glama](https://glama.ai/mcp/servers/hfcveypry0)
- **Repository:** <https://github.com/VisionAIrySE/XFMS>

## 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": "visionairyse-xfms"
    }
  }
}
```

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