# fastevals

> fastevals — semenovdv-fastevals. Use this tool when you need to evaluate the performance of large language models (LLMs) in a provider-agnostic manner, solving problems of inconsistent evaluation metrics and costly validation processes. It provides a standardized interface for inputs such as datasets and evaluators, and outputs structured validation results and honest cost metrics. Ideal for use cases where accurate and efficient LLM evaluation is crucial, such as model development and comparison.

Canonical page: https://skillsregistry.net/skills/semenovdv-fastevals  
JSON: https://api.skillsregistry.net/v1/skills/semenovdv-fastevals

## Description

Give your AI agents an evaluation tool - provider-agnostic LLM eval runner with an MCP server for Claude, structured output validation, datasets, evaluators and honest cost metrics

## Trust

- **Trust score (0–1):** 0.81
- **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/semenovdv/fastevals)

## 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": "semenovdv-fastevals"
    }
  }
}
```

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