by CMarsRover · Agent Tool · ★ 33
SciAgentGym: Benchmarking Multi-Step Scientific Tool-use in LLM Agents 📃 Paper • 🤗 Data & Models • 🔧 Toolkits We present SciAgentGym, the first benchmark environment for evaluating LLM agents' capability in multi-step scientific tool-use. SciAgentGym provides a comprehensive suite of scientific tools across multiple disciplines, enabling rigorous evaluation of how well LLMs can solve complex scientific problems through sequential tool invocation. Overview Complex scientific problems often require multiple steps of computation, each involving specialized domain tools.
| Stars | 33 |
| Forks | 4 |
| Language | Python |
| Category | Agent Tool |
| License | Apache-2.0 |
| Quality Score | 65.7684342053375/100 |
| Open Issues | 3 |
| Last Updated | 2026-07-05 |
| Created | 2025-08-26 |
| Platforms | python |
| Est. Tokens | ~15k |
These tools work well together with SciAgentGYM for enhanced workflows:
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SciAgentGYM is Code for Paper: Benchmarking Multi-step Scientific Tool-use in LLM Agents. It is categorized as a Agent Tool with 33 GitHub stars.
SciAgentGYM is primarily written in Python.
You can find installation instructions and usage details in the SciAgentGYM GitHub repository at github.com/CMarsRover/SciAgentGYM. The project has 33 stars and 4 forks, indicating an active community.
SciAgentGYM is released under the Apache-2.0 license, making it free to use and modify according to the license terms.