by expectedparrot · Agent Tool · ★ 485
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Expected Parrot Domain-Specific Language (EDSL) EDSL makes it easy to conduct computational social science and market research with AI. Use it to design and run surveys and experiments with many AI agents and large language models at once, or to perform complex data labeling and other research tasks. Results are formatted as specified datasets that can be replicated at no cost, and come with built-in methods for analysis, visualization and collaboration. Getting started Run to install the package. See instructions. Create an account to run surveys at the Expected Parrot server and access a universal remote cache of stored responses for reproducing results. Choose whether to use your own keys for language models or get an Expected Parrot key to access all available models at once. Securely manage keys, expenses and usage for your team from your account. Run the <a href="htt
| Stars | 485 |
| Forks | 78 |
| Language | Python |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 64.9987228427722/100 |
| Open Issues | 49 |
| Last Updated | 2026-08-08 |
| Created | 2024-01-02 |
| Platforms | python |
| Est. Tokens | ~15k |
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edsl is Design, conduct and analyze results of AI-powered surveys and experiments. Simulate social science and market research with large numbers of AI agents and LLMs.. It is categorized as a Agent Tool with 485 GitHub stars.
edsl is primarily written in Python. It covers topics such as anthropic, data-labeling, deepinfra.
You can find installation instructions and usage details in the edsl GitHub repository at github.com/expectedparrot/edsl. The project has 485 stars and 78 forks, indicating an active community.
edsl is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to edsl on Agent Skills Hub include autollm, palico-ai, captain-claw. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.