{
  "title": "Self-Improvement Agent Harness: A Deterministic SIA Exemplar",
  "version": "0.1.0",
  "doi": "10.5281/zenodo.20453880",
  "doi_url": "https://doi.org/10.5281/zenodo.20453880",
  "zenodo_record": "https://zenodo.org/records/20453880",
  "record_id": "20453880",
  "publication_date": "2026",
  "resource_type": {
    "title": "Journal article",
    "type": "publication",
    "subtype": "article"
  },
  "creators": [
    {
      "name": "Daniel Ari Friedman",
      "affiliation": "Active Inference Institute",
      "orcid": "0000-0001-6232-9096"
    }
  ],
  "description": "Abstract This exemplar documents template_sia, a deterministic implementation of the Self-Improvement Agent (SIA) harness contract described in . The default pipeline replays fixture-backed generations for the mini_classify task; opt-in live mode runs bounded target subprocesses and optional Ollama-backed meta/feedback steps. Run snapshot. Task mini_classify, run 1, 3 generation(s), live=false. Final accuracy=0.8333 over 6 held-out samples. Values are injected by scripts/z_generate_manuscript_variables.py after analysis. Keywords: self-improvement agents, benchmark harness, reproducible evaluation, agent loops --- Associated artifacts GitHub release: v0.1.0 (https://github.com/docxology/template/releases/tag/v0.1.0) PDF SHA-256: 7087b6d1dd2e6192b24055408935201c27d7e19ba26267a366b20b2c71b7a721",
  "keywords": [
    "self-improvement agents",
    "benchmark harness",
    "reproducible research",
    "agent evaluation"
  ],
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      "name": "Friedman_2026_Selfimprovement_7087b6d1.pdf",
      "size_bytes": 42046,
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  "related_resources": [],
  "github_repo": "",
  "source": "zenodo-only",
  "checked_at": "2026-05-30T18:56:00Z"
}