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Unspaghettit

v0.9.0 Feature

This release adds 5 notable features for engineering teams evaluating rollout.

✓ No known CVEs patched
Read the diff → Tool health → What is this tool? →

✓ No known CVEs patched in this version

Summary

AI summary

Introduces source‑trust ranking, action outcome modeling, sharper verification techniques, prose acceptance criteria, and core feature pillars.

Full changelog

Make the model's own claims trustworthy, then start catching the defects a green model used to hide.

Highlights

  • Source trust & extraction completeness — rank sources by authority (contradictions resolve by weight, not reading order), record two that disagree as a first-class conflict, stage behavior candidates before committing them, and measure the share of each source that actually reached the model (get_source_coverage).
  • Model what actually happens — first-class action outcomes (declined, timed out, partial), external dependencies + the invoke_operation effect with their timeout/retry/idempotency contract, event delivery guarantees (a required handler failure fails the emitter; transactional rolls it back), and scoped invariant relaxation for repair actions.
  • Sharper verification — bounded model checking now explores parameter domains (not just defaults), an honest confidence matrix in score_feature (the weakest dimension is the headline), decision-table analysis in get_spec_gaps, and an evidence-first unspa check --strict gate.
  • Feature-level prose acceptance criteria — capture Given/When/Then edge cases as documentation, the honest complement to model-checked scenarios: rendered, searchable, carried in the model, but never simulated or scored.
  • Core features — declare a project's product pillars once and group features under them precisely: a reserved core: tag backed by a project-level registry, so you filter by core feature instead of by a sea of tags.

Full detail in CHANGELOG.md.

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Beta — feedback welcome: [email protected]