Same Statement, Different Script: Taiwan responses in decision models

A benchmark of Jev and other decision models on trolley-problem states, with runners, raw answers and analysis in one repository. The v1 snapshot covers 1,098 states and the October 2026 v2 run has 14 models on 5,240 frozen states.

A reproducible experimentation framework and report series for Jev: it runs shared tasks at scale across benchmarks, routing and numeric prediction, and publishes bilingual findings on where the model holds up and where it does not.

AkitaOnRails' study documentation and benchmark harness for Jev-like decision models: frozen inputs, inspectable expected answers, raw response archives and reproducible scoring compare TypeSafe Jev with Decision-1, OpenAI Decisions, Clef, Decision 3.0, Laya, Kev, Eikos, Jebadiah, Mapika Decider and GLiNER.

A Python experiment that adapts Gemma 4 E4B for System One-style decisions: one call takes a situation and a fixed answer list and returns a probability per answer, with per-dataset adapters and held-out results across four datasets.

One Python interface for evaluating what LLM apps and agents say and do. Its CascadeEvaluator asks a decision model first — Jev, OpenAI's Decisions API, or any model served at /v1/systemone — keeps confident answers, and sends only the rest to an LLM judge.

A CLI from Pinecone's DevRel team for testing Agent Skills and docs against tasks: run tasks across Claude, Copilot and Gemini in local or Modal sandboxes, compare with-skill, without-skill and with-docs variants, and grade with Claude or a TypeSafe System One backend.