hypogenic

# HypoGeniC ## Scope and scientific boundary This skill covers the ChicagoHAI software repository `ChicagoHAI/hypothesis-generation` and PyPI package `hypogenic`. HypoGeniC iteratively proposes and scores textual patterns from labeled data; HypoRefine adds literature-derived information; union workflows combine banks. Keep these boundaries explicit: - The output is a bank of **candidate textual hypotheses and task-prediction statistics**. It is not experimental confirmation, causal evidence, a clinical conclusion, or proof of scientific novelty. - Predictive accuracy on held-out examples assesses task utility, not truth of a mechanism. Independent scientific validation still needs domain review, suitable controls, preregistered tests where appropriate, and new evidence. - For researcher-led formulation of mechanisms and falsifiable predictions, use `../hypothesis-generation/SKILL.md`. For open-ended ideation, use the scientific brainstorming skill. ## Default workflow: local review first Never start a model call automatically. 1. Classify the request: HypoGeniC software use, general hypothesis formulation, or downstream scientific validation. 2. Record the exact package, source, dataset, model/provider, destination, split policy, output path, and budgets. 3. Validate the local run policy and official task config. 4. Audit dataset checksums, schemas, duplicates, and split leakage. 5. Generate a bounded cost/run plan. Review provider retention and curre...