{
  "title": "Jev in Practice: A Composable Python Toolkit for TypeSafe's System One Decision Model",
  "version": "0.6.0",
  "doi": "10.5281/zenodo.22816187",
  "doi_url": "https://doi.org/10.5281/zenodo.22816187",
  "zenodo_record": "https://zenodo.org/records/22816187",
  "record_id": "22921974",
  "publication_date": "2026-09-23",
  "resource_type": {
    "title": "Software",
    "type": "software"
  },
  "creators": [
    {
      "name": "Friedman, Daniel Ari",
      "affiliation": "Active Inference Institute",
      "orcid": "0000-0001-6232-9096"
    }
  ],
  "description": "<p>Jev is TypeSafe's flagship <em>System One</em> decision model: instead of generating text, it answers typed questions (Choice, Score, Noul) about a state with calibrated probabilities that software can branch on directly. This work presents <code>daf-jev</code>, an open, modular, composable Python toolkit for the Jev API, together with a live-API characterization of the model. The package layers ergonomic question builders, a decision-composition library (confidence gates, tiered routing, composite scoring), a concurrent corpus evaluator, a calibration module, a CLI, an agent skill, and a Model Context Protocol (MCP) server over a thin typed client. Live benchmarks show that batching questions into one call is faster and cheaper than sequential calls (up to ~18x speedup and ~4x fewer tokens), that decision pipelines complete within the model's millisecond envelope, and that reported confidence is self-consistent across repeated evaluations. All numbers in the accompanying manuscript are generated from benchmark artifacts; the full provenance chain (hashed documentation snapshot, figure registry, validation receipts) is machine-checked.</p>",
  "keywords": [],
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  "related_resources": [
    {
      "type": "repository",
      "url": "https://github.com/docxology/daf-jev"
    }
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  "github_repo": "docxology/daf-jev",
  "github_release_url": "https://github.com/docxology/daf-jev/releases/tag/v0.6.0",
  "release_tag": "v0.6.0",
  "release_name": "v0.6.0 — Jev as a factor source for graphical models",
  "pdf_sha256": "",
  "pairing_confidence": "strong",
  "pairing_evidence": [
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  "checked_at": "2026-09-24T18:29:58Z"
}