llm-benchmark

What problem does it solve?

Design rigorous, statistically powered benchmarks to evaluate LLM prompts and configurations, ensuring experiments produce actionable, unbiased conclusions.

Core Features & Use Cases

• Rigorous experimental design templates for policy vs mechanism benchmarks
• Data leakage prevention guidance to keep prompts domain-blind and test data separate
• Per-turn metrics and statistical analysis guidance to interpret results across models and tasks
• Use cases include prompt ablation studies, A/B testing prompts, and design of held-out test suites

Quick Start

Run a baseline benchmark on your prompts and report observed pass rates, per-turn metrics, and recommended sample sizes.