# AI use cases for Awesome AI Scientist (Omni-Scientist/Awesome-AI-Scientist) Repo: [Omni-Scientist/Awesome-AI-Scientist](https://github.com/Omni-Scientist/Awesome-AI-Scientist) | Use cases: 4 | Page: https://dedupedai.com/use-cases/omni-scientist-awesome-ai-scientist/ A curated GitHub list of papers, AI Scientist systems, benchmarks, datasets and open-source platforms for AI that does science. This file holds every use case of this repo. Each one starts with a "## " heading and ends with its URL. - Run an open AI Scientist system on a test question: https://dedupedai.com/use-cases/omni-scientist-awesome-ai-scientist/run-open-ai-scientist-pipeline/ - Shortlist benchmarks to test a science agent: https://dedupedai.com/use-cases/omni-scientist-awesome-ai-scientist/shortlist-benchmarks-for-science-agent/ - Find datasets and environments for a science agent: https://dedupedai.com/use-cases/omni-scientist-awesome-ai-scientist/find-datasets-for-science-agent-training/ - Review safety and policy readings for autonomous research: https://dedupedai.com/use-cases/omni-scientist-awesome-ai-scientist/review-safety-policy-for-autonomous-research/ ## How to run an open AI Scientist system on a test question with Awesome AI Scientist Repo: [Omni-Scientist/Awesome-AI-Scientist](https://github.com/Omni-Scientist/Awesome-AI-Scientist) | Difficulty: Advanced | Time: 3 hours | Basis: From the README Pick a linked end-to-end system and run it on one small research question. **Who it is for:** A graduate student or ML engineer who wants to see how an end-to-end AI Scientist behaves before using one in their own lab. **The problem:** There are many AI Scientist systems, and it is hard to tell which ones have public code you can run. **The outcome:** You have one working end-to-end system, a short note on its setup effort, and a sample output from a test question. ### Steps 1. Open the End-to-End AI Scientists section of the README. 2. Pick an entry whose badge links to a GitHub repository, such as The AI Scientist or data-to-paper. 3. Open that repository and read its own README, because this list does not give setup steps. 4. Clone the chosen repository with git and create a Python environment for it. (inferred, check the README) 5. Run the project on one small test research question and save the output for review. ### Prompt to paste into your agent ```text Using the README of Omni-Scientist/Awesome-AI-Scientist, list the End-to-End AI Scientists entries that link to a GitHub repository and fit the research question . Return each system name, its paper link and its repository link, and confirm each repository link appears in the README before reporting it. ``` ### Caveat This list links to projects but does not include their setup steps, so each project's own README decides what you need to install. Risk, remote script: Linked research systems run code and may call external services, so review each project's code before running it on your machine. Dual-use notice: only use this on software, sites and systems you own or are authorized to test. Disclaimer: Third-party repos we don't own or vouch for. AI-generated use cases can be wrong: review everything and run at your own risk. Full text: https://dedupedai.com/disclaimer/ URL: https://dedupedai.com/use-cases/omni-scientist-awesome-ai-scientist/run-open-ai-scientist-pipeline/ ## How to shortlist benchmarks to test a science agent with Awesome AI Scientist Repo: [Omni-Scientist/Awesome-AI-Scientist](https://github.com/Omni-Scientist/Awesome-AI-Scientist) | Difficulty: Beginner | Time: 30 minutes | Basis: From the README Pick benchmarks and leaderboards that fit the science task your agent handles. **Who it is for:** An ML engineer who has built or chosen an agent for a science task and needs fair tests before claiming it works. **The problem:** Choosing among dozens of benchmarks is slow, and it is unclear which ones match a given domain. **The outcome:** You have a short list of two or three benchmarks, each with a paper link and a leaderboard reference, ready for your evaluation plan. ### Steps 1. Open the Benchmarks & Evaluation section and note entries that match your task area. 2. Open the Leaderboards & Live Trackers section to see where results for those benchmarks are posted. 3. Open each candidate's paper link and check what it measures and how it is scored. 4. Write down the two or three benchmarks that best fit your agent's inputs and outputs. ### Prompt to paste into your agent ```text Using the README of Omni-Scientist/Awesome-AI-Scientist, find the Benchmarks & Evaluation entries that match . For each match, give the name, paper link and any leaderboard listed in the Leaderboards & Live Trackers section, and state one scoring detail from the paper. ``` ### Caveat The list points to benchmark papers and leaderboards, so you still need to read each paper to confirm what it scores. Dual-use notice: only use this on software, sites and systems you own or are authorized to test. Disclaimer: Third-party repos we don't own or vouch for. AI-generated use cases can be wrong: review everything and run at your own risk. Full text: https://dedupedai.com/disclaimer/ URL: https://dedupedai.com/use-cases/omni-scientist-awesome-ai-scientist/shortlist-benchmarks-for-science-agent/ ## How to find datasets and environments for a science agent with Awesome AI Scientist Repo: [Omni-Scientist/Awesome-AI-Scientist](https://github.com/Omni-Scientist/Awesome-AI-Scientist) | Difficulty: Beginner | Time: 45 minutes | Basis: From the README Locate datasets, corpora and environments to train or test an agent on science tasks. **Who it is for:** A data scientist building a science agent who needs data and sandbox environments that match a specific field. **The problem:** Science datasets and environments are scattered across papers, so finding usable ones takes long searches. **The outcome:** You have a shortlist of datasets and environments with links, filtered to your field, ready for a data-access check. ### Steps 1. Open the Datasets, Corpora & Environments section of the README. 2. Scan the entries for the field you need, such as chemistry, biology or materials. 3. Open each candidate and confirm the license and access terms on its own page. 4. Record the three best candidates with their links for your project notes. ### Prompt to paste into your agent ```text Using the README of Omni-Scientist/Awesome-AI-Scientist, list the Datasets, Corpora & Environments entries relevant to . Return each name and link, and verify on each linked page that the access terms are stated before you include it. ``` ### Caveat The README lists datasets and environments without access terms, so you must check each linked source yourself. Dual-use notice: only use this on software, sites and systems you own or are authorized to test. Disclaimer: Third-party repos we don't own or vouch for. AI-generated use cases can be wrong: review everything and run at your own risk. Full text: https://dedupedai.com/disclaimer/ URL: https://dedupedai.com/use-cases/omni-scientist-awesome-ai-scientist/find-datasets-for-science-agent-training/ ## How to review safety and policy readings for autonomous research with Awesome AI Scientist Repo: [Omni-Scientist/Awesome-AI-Scientist](https://github.com/Omni-Scientist/Awesome-AI-Scientist) | Difficulty: Beginner | Time: 45 minutes | Basis: From the README Collect the safety, ethics and policy sources on AI systems that run research. **Who it is for:** A research lead or policy writer who must set rules for using autonomous AI in a lab or team. **The problem:** Autonomous research agents raise safety and ethics questions, and the sources on them are spread out. **The outcome:** You have a reading list of about five safety, ethics or policy sources with a one-line note on each. ### Steps 1. Open the Safety, Ethics & Policy section of the README. 2. Read the titles and select the five sources closest to your team's use case. 3. Open each linked paper and note the risk or rule it discusses. 4. Draft a short summary of the common points for your team. ### Prompt to paste into your agent ```text Using the README of Omni-Scientist/Awesome-AI-Scientist, pick five entries from the Safety, Ethics & Policy section that relate to . Return each title, link and a one-sentence note on the risk it covers, and check that each note matches the linked paper's abstract. ``` ### Caveat The section lists sources to read, so the policy conclusions come from those sources, not from this list. Dual-use notice: only use this on software, sites and systems you own or are authorized to test. Disclaimer: Third-party repos we don't own or vouch for. AI-generated use cases can be wrong: review everything and run at your own risk. Full text: https://dedupedai.com/disclaimer/ URL: https://dedupedai.com/use-cases/omni-scientist-awesome-ai-scientist/review-safety-policy-for-autonomous-research/