benchmark-guide

Complete guide to all 60+ evaluation tasks in lm-evaluation-harness, what they measure, and how to interpret results.

Skills
AI research
1

What it does and how to use it

A skill that teaches Claude Code to do ai research tasks well. It is packaged knowledge the model uses whenever it is relevant.

Install the skill (command above).
In Claude Code, describe what you need - the skill turns on by itself when the context fits.
No commands to memorize: you talk in plain language and the skill does the rest.

Install (Claude Code)

mkdir -p .claude/skills/benchmark-guide && curl -fsSL https://doutorai.pt/data/lib/skills__benchmark-guide.md -o .claude/skills/benchmark-guide/SKILL.md

Paste this command into the terminal, in your project folder, and the component installs automatically.

Content

# Benchmark Guide

Complete guide to all 60+ evaluation tasks in lm-evaluation-harness, what they measure, and how to interpret results.

## Overview

The lm-evaluation-harness includes 60+ benchmarks spanning:
- Language understanding (MMLU, GLUE)
- Mathematical reasoning (GSM8K, MATH)
- Code generation (HumanEval, MBPP)
- Instruction following (IFEval, AlpacaEval)
- Long-context understanding (LongBench)
- Multilingual capabilities (AfroBench, NorEval)
- Reasoning (BBH, ARC)
- Truthfulness (TruthfulQA)

**List all tasks**:
```bash
lm_eval --tasks list
```

## Major Benchmarks

### MMLU (Mass

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