Criticality Spectrometer v0.1.1

Hardening release focused on reproducible public artifacts, stricter model validation, and a trustworthy distribution path.

Added

• Self-identifying JSON reports with instrument version, schema versions, model SHA-256, horizons, and run configuration
• Public and packaged result schemas
• One deterministic regeneration command for the AI models, parity ledger, complete results bundle, and README figure
• CI freshness enforcement for generated and untracked artifacts
• Narrated ten-node tutorial and Python API quickstart
• --version, documented exit codes, py.typed, and Python 3.13 coverage
• OIDC-based PyPI release workflow with no long-lived API tokens

Hardened

• Direct self-satisfaction now raises ModelError
• Dependent outcome sources emit ModelWarning
• Explicit horizons are sorted and deduplicated
• OR-gap comparison reuses computed AND survival through one public implementation
• Public and packaged schemas are kept byte-identical by tests

Reproducibility

The committed AI models, reports, parity ledger, and README figure regenerate byte-clean from source. The source and clean-wheel suites both pass 72 tests.

Known boundaries

This remains a single-domain alpha. It does not infer dependencies or activation times, make causal claims, or provide connectivity-only or k-of-n relations. See the method, non-claims, and worked-example parity analysis.

Criticality Spectrometer v0.1.0

Criticality Spectrometer measures node-removal impact as a curve across adaptation horizons in systems with explicit AND/OR requirements.

Included

• Case-free Python engine and validated JSON model contract
• Group-targeted substitutes with activation times
• served_sinks and ordered mission outcomes
• Deterministic CLI output and conservative curve classes
• Seven-node canonical fixture
• Audited 52-node AI-compute worked example with parity and evidence ledgers
• 56 semantic, CLI, packaging, and empirical-parity tests
• Clean-wheel installation and deterministic-output CI gate

Known boundaries

This alpha release has one empirical domain. It does not infer dependencies or activation times, make causal claims, or convert curve classes into policy prescriptions. The v0.1 contract has no connectivity-only edge relation; the worked example records where that limitation matters.

See the method, non-claims, and worked-example parity analysis.