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Spanda Normative Harness

Deterministic micro-demos for validating Spanda normatives with schema-validated JSONL outputs.

Quickstart

source .venv/bin/activate
python3 harness/run_demo.py --demo demo27_no_narrative_projection --mode proof
python3 harness/run_demo.py --demo demo27_no_narrative_projection --mode break

Run all demos

source .venv/bin/activate
for d in demos/*; do
  demo_id="$(basename "$d")"
  python3 harness/run_demo.py --demo "$demo_id" --mode proof
  python3 harness/run_demo.py --demo "$demo_id" --mode break
done

Normatives coverage

Paper 8 (Spanda architectural documentation) — Normative Spec v0.2 — DOI: 10.5281/zenodo.18791708 https://doi.org/10.5281/zenodo.18791708

N01–N30 are currently covered by 31 demos (N11 has two demos).

Determinism contract

  • No network calls in demo logic.
  • No randomness in demo logic.
  • Same fixture input must produce identical output behavior.
  • Output events are validated against harness/schema.json.
  • Every demo result must include explicit rationale and evidence.

Repo structure

.
├── harness/      # deterministic runner + JSON schema
├── demos/        # one folder per micro-demo (proof.json, break.json, demo.py, README.md)
├── normatives/   # normative references and mapping notes
├── logs/         # local-only generated JSONL outputs
└── tasks/        # local-only scratchpad (not tracked)

Notes

  • logs/ contains generated deterministic JSONL outputs and is local-only.
  • tasks/ is a local-only scratchpad and is not tracked.

License

This project is licensed under Creative Commons Attribution–NonCommercial 4.0 International (CC BY-NC 4.0).
See the LICENSE file for details.

Contact

  • GitHub: @putmanmodel
  • Email: putmanmodel@pm.me
  • BlueSky: @putmanmodel.bsky.social
  • X / Twitter: @putmanmodel
  • Reddit: u/putmanmodel

About

Deterministic micro-demos that prove/falsify Spanda normatives (N01–N30). Each demo has proof/break fixtures and emits replayable JSONL decisions with evidence + rationale—an executable harness for constraint-bound, stratified agent architectures.

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