by microsoft · Agent Tool · ★ 1.1k
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🔒 Is ToRA safe to install? View the security audit →
ToRA: A Tool-Integrated Reasoning Agent [🌐 Website] • [📜 Paper] • [🤗 HF Models] • [🐱 GitHub] [🐯 Gradio Demo] -- [🐦 Twitter] • [💬 Reddit] • [🍀 Unofficial Blog] Quick Start • -- <!-- <a href="#%E
git clone https://github.com/microsoft/ToRA.git && cd ToRA/srcTaken from the project's README on GitHub. Check the security audit before running it.
No red flags found in any of the 11 categories — no credential harvesting, no data exfiltration, no curl-pipe-shell installer. Scanned against the SlowMist agent-security taxonomy, refreshed every 8 hours. Full audit →
| Stars | 1,124 |
| Forks | 79 |
| Language | Python |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 67.8410029995516/100 |
| Open Issues | 7 |
| Last Updated | 2024-02-22 |
| Created | 2023-09-27 |
| Platforms | python |
| Est. Tokens | ~1099k |
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ToRA is ToRA is a series of Tool-integrated Reasoning LLM Agents designed to solve challenging mathematical reasoning problems by interacting with tools [ICLR'24].. It is categorized as a Agent Tool with 1.1k GitHub stars.
ToRA is primarily written in Python. It covers topics such as autonomous-agents, language-model, llm.
The README on GitHub (github.com/microsoft/ToRA) gives: git clone https://github.com/microsoft/ToRA.git && cd ToRA/src. Usage details are in the same README.
ToRA is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to ToRA on Agent Skills Hub include LLM-Tool-Survey, gptme, langroid. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.
Grades come from a rule-based scan built on the SlowMist agent-security taxonomy, covering 11 red-flag categories including credential harvesting, data exfiltration, and curl | sh installers. It is a first-layer scan, not a manual audit — we say so rather than overstate it.
The scale of the problem is documented independently: Liu et al. (2026), in a study of 31,132 agent skills, report that 26.1% contain security vulnerabilities. Our own full-catalog census is published as a citable open dataset.
Sources & who's responsible: