Who it is forA researcher or evaluator who wants to see what EAR produces before setting up any model account.
The problemSetting up live research tools takes time, and it is hard to judge the workbench from a repository page alone.
The outcomeA local studio page where you can search the idea tree, inspect a critique, download a proposal, check a proof and download a paper, and trace reviewer evidence.
What you need first
- Python 3.10 or newer
- git, to clone the repository
- For live research only: an authenticated Codex or Claude setup and the module dependencies described in docs/getting-started.md
Steps
- Install Python 3.10 or newer.
- Run
git clone https://github.com/liyingze07-svg/EffectiveAutoResearch-EAR-.git EAR - Run
cd EAR - Run
python3 -m ear demo studio - Open the studio page the command starts, select a module, and inspect or download its output.
- Run
python3 -m ear demo checkto validate the idea trace and synthetic rebuttal wiring.
Prompt for your agent
Clone the repo liyingze07-svg/EffectiveAutoResearch-EAR- into <target-folder>, then run `python3 -m ear demo check` from inside it. Report the output of the check, and state whether it validated the idea trace and synthetic rebuttal wiring. Do not claim any live model result, since the demo uses authored examples.
Caveat. The demo uses authored examples, so its outputs show the workflow shape and are not evidence of live research results.
Get 5 new use cases every morning. Free, one short email, unsubscribe anytime.
Get them freeShare: X LinkedIn Hacker News Email Copy link
Disclaimer
Deduped lists open-source repositories that belong to other people. We do not own, maintain, audit, or vouch for any of them, and a repo appearing here is not an endorsement or a safety check. The use cases, steps, and prompts are written by AI and may be incomplete, outdated, or just wrong. Where a use case is marked "Seen in the wild", we link to public posts where someone described something similar, but we have not verified those posts and the use case itself is still our AI's own write-up. Use all of this at your own risk. Only run code, commands, or agents on systems and accounts you are authorized to use, and read the code and every command before you run it, especially anything that touches credentials, files, or the network. Nothing here is professional, security, legal, or financial advice. All trademarks and project names belong to their respective owners, and their use here does not imply affiliation. Content is provided as is, without warranties of any kind. Found a mistake, a safety problem, or something you want removed? Email [email protected] and we will look at it promptly. Full disclaimer page