What it is
hunch turns Jev Choice, Score, and Noul questions into Python functions over strings, lists, and pandas DataFrames. It provides verbs like classify, score, check, where, extract, pick, rank, and verify, with request deduplication, caching, and optional LLM escalation for unsure rows.
How it uses Jev
Jev judges each row by answering typed questions: Choice picks one option from a closed set, Score returns a position on ordered levels, and Noul gives the probability a statement is true. hunch sends one request per distinct row, caches answers, and returns plain answers or full distributions with shape labels (sure, split, unsure) that code can branch on.
Primitives:choicescorenoul
Technique worth stealing
One request per distinct row, with several questions about the same row batched together, and answers cached so re-running costs nothing.
Try it
pip install hunch-jev
Evidence
Each line is one question put to Jev about the README. ≥ 0.60 reads as yes, ≤ 0.40 as no; in between Jev is not making a call.
- Jev-centricyes0.94
- Shows a System One patternyes0.86
- Handles uncertaintyyes0.82
- Measuredno0.04
- Runnableyes0.98
- Worth recommendingunclear0.51
- Model replicano0.09
- Problem scopescore on a 0–2 scale1.30
- About Jevyes0.98
Signals by Jev jev-1.13.0, card written by DeepSeek V4.1 Flash from the README on 23 Sept 2026.