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About hypogenic
hypogenic
Plans and audits use of ChicagoHAI HypoGeniC/HypoRefine
hypogenic is an agent skill for planning and auditing the use of HypoGeniC and HypoRefine, tools from the ChicagoHAI project for language-model-assisted hypothesis generation from labelled text datasets. It covers the ChicagoHAI hypothesis-generation repository and the hypogenic package on PyPI. HypoGeniC iteratively proposes textual patterns from labelled data and scores them. HypoRefine adds information derived from the literature, and union workflows combine banks of hypotheses from both. The skill keeps its boundaries explicit: the outputs are candidate patterns to be tested, not established findings, and they depend on the quality and labelling of the data you supply. Use it when you have a labelled text dataset and want candidate explanations generated and scored, or when you want a plan that checks how an existing HypoGeniC or HypoRefine run was set up. The skill is part of the k-dense-ai scientific agent skills repository on GitHub, which has about 49,600 stars. The listing shows it as free, and it has about 1,800 installs. Its security audits show passes from Gen Agent Trust Hub and Socket, with a warning from Snyk.
- Price
- Free
- Made by
- k-dense-ai
- Category
- AI Skills
- Website
- github.com/k-dense-ai/scientific-agent-skills/hypogenic