Skip to content
BeClaude

NatureBench

New
54GitHub TrendingGeneralby FrontisAI

NatureBench: Can Coding Agents Match the Published SOTA of Nature-Family Papers?

First seen 6/24/2026

Summary

NatureBench evaluates coding agents against published state-of-the-art results from Nature-family papers, helping developers benchmark their AI's ability to reproduce complex scientific experiments and data analysis pipelines.

  • It provides a standardized test suite to measure how well coding agents match rigorous scientific methodologies.

Install & Usage

1
Create the agents directory
mkdir -p .claude/agents
2
Save the agent file

Add the configuration to .claude/agents/naturebench.md

3
Invoke with @agent-name
@naturebench

Use Cases

Benchmark a coding agent's ability to reproduce data analysis from a Nature paper on climate modeling.
Test if an AI can implement the exact statistical methods used in a published Nature Genetics study.
Evaluate an agent's performance on replicating computational biology experiments from Nature Methods.
Assess how well a coding agent follows the experimental protocol from a Nature Communications paper.
Compare multiple coding agents on their accuracy in reproducing Nature paper figures and tables.
Validate that an agent's code produces results within the error margins reported in the original publication.

Usage Examples

1

/naturebench run --paper 'Nature 2023 climate model' --task reproduction

2

Evaluate my agent on NatureBench using the paper 'Deep learning in drug discovery' from Nature Reviews Drug Discovery.

3

/naturebench compare --agents claude,gpt4 --papers 'Nature Biotechnology 2022, Nature Medicine 2023'

View source on GitHub
agent

Security Audits

LicenseUnknownSourceWarnRepositoryPass

Frequently Asked Questions

What is NatureBench?

NatureBench evaluates coding agents against published state-of-the-art results from Nature-family papers, helping developers benchmark their AI's ability to reproduce complex scientific experiments and data analysis pipelines. It provides a standardized test suite to measure how well coding agents match rigorous scientific methodologies.

How to install NatureBench?

To install NatureBench: create the agents directory (mkdir -p .claude/agents), then add the config to .claude/agents/naturebench.md. Finally, @naturebench in Claude Code.

What is NatureBench best for?

NatureBench is a agent categorized under General. It is designed for: agent. Created by FrontisAI.

What can I use NatureBench for?

NatureBench is useful for: Benchmark a coding agent's ability to reproduce data analysis from a Nature paper on climate modeling.; Test if an AI can implement the exact statistical methods used in a published Nature Genetics study.; Evaluate an agent's performance on replicating computational biology experiments from Nature Methods.; Assess how well a coding agent follows the experimental protocol from a Nature Communications paper.; Compare multiple coding agents on their accuracy in reproducing Nature paper figures and tables.; Validate that an agent's code produces results within the error margins reported in the original publication..