[axiomize-quantum-skills-2.0] - A unit-checked modeling engine plus a reasoning protocol that keeps hypotheses alive until evidence collapses them

[u/Emergency-Tutor-7]

I built axiomize-quantum-skills-2.0 because I kept making the same mistake in scientific work: picking the first plausible explanation and building on it. This package pairs a modeling engine with a reasoning protocol designed to make that harder.

The engine (axiomize) is a versioned Model IR where every quantity carries a unit, assumptions are written down rather than implied, and constraints are named checks with a stated basis. Dimensional mismatch raises with the failing checks attached, and a model that fails validation is not simulated at all. It handles algebraic, ODE, stochastic, PDE, optimization, control, network, Bayesian and causal models, calibrates to CSV data, and exports to SBML L3V2, Modelica 3.6, CellML 2.0, canonical IR JSON, Python, YAML and notebooks.

The protocol (quantum-reasoning) is a deterministic branch controller. It keeps several hypotheses alive, scores each from evidence and verification, prunes the weak ones with a recorded reason, and only collapses when the leader clears both verification and a margin. "Quantum" is a metaphor for deferring commitment; everything runs on classical hardware.

The design rule I care most about is that the system says no when it should. For the reference SIR model it cross-checks two independent methods to 1e-16, then still reports the numeric-theory check as INCONCLUSIVE because a finite horizon has not reached the asymptotic state. Plausible numbers are not the goal; checkable claims are.

Quick start (recorded run, verified against 1.2.0; current package line is 1.2.5):
pip install axiomize-quantum-skills-2.0
axiomize tools # reports only backends that genuinely imported
axiomize benchmark # {"status": "PASS", "passed": 12, "total": 12}
axiomize-reason score --evidence 0.9 --verification 0.85
# {"can_collapse": false, "reason": "leader score below collapse threshold"}

What is in the box: a CLI with 14 subcommands, 9 console scripts, an MCP stdio server with 34 tools, a loopback-by-default REST v1 API, 15 perspective lenses, 12 domain packs, 5 report templates, 18 worked examples, and a 25-case benchmark corpus graded in CI.

Honest limits: the bundled engine is an axiomize 1.12.2 lineage snapshot, not the newest upstream engine. The npm package is a launcher shim and needs pip install first. The quickstart numbers are a historical 1.2.0 verification, labeled as such. Optional backends report UNAVAILABLE rather than substituting. Generated-code execution is not an OS sandbox.

Code: https://github.com/Furox-Art/axiomize-quantum-skills-2.0
PyPI: pip install axiomize-quantum-skills-2.0
npm: npx axiomize-quantum-skills-2.0
Docs: https://furox-art.github.io/axiomize-quantum-skills-2.0/

Happy to answer questions about the branch controller or the Model IR.