Jev Dspy

Six small Python files that build one coding agent step by step on DSPy's RLM sandbox, with Jev answering closed questions — command safety, tool choice, history relevance, delegation — and plain Python owning the thresholds.

DSPy's experimental decision types put Jev behind one Predict: Noul, Choice, and Score annotations, per-field thresholds and cuts, and adapter translation that derives results from probability evidence.

Unofficial companion to dspy-typesafeify that records and replays TypeSafe calls to measure calibration, selective risk, confidence-gated abstention, latency, tokens and modeled cost for Jev decisions.