data-integrity-spans-architecture

OUT derived (depth 2)

Data integrity is enforced across all three architectural layers: clean layer boundaries prevent cross-cutting mutations, snapshot persistence ensures atomic state transitions, and conservative staleness checking gates CI pipelines.

Summary

The system protects data correctness through three reinforcing mechanisms: clean separations between layers stop unintended side effects, saving works as all-or-nothing snapshots so you never end up with half-updated state, and the staleness checker acts as a conservative gatekeeper that blocks CI pipelines rather than risk letting stale data through. This belief is currently OUT, meaning at least one of those three properties no longer holds, which weakens the overall data integrity guarantee.

Justifications

SL — Each architectural layer contributes a distinct integrity guarantee that together cover the full stack from data model through persistence to CI

Antecedents (all must be IN):

  • three-layer-stack-has-clean-boundaries — The architecture enforces strict layer separation: pure data model at bottom, context-managed API with dict returns in the middle, and pure-formatter CLI at the top
  • persistence-is-snapshot-not-incremental — The storage layer operates as a full snapshot: save replaces all rows, load trusts stored values without re-propagation, and the dependents index is rebuilt from scratch
  • staleness-is-conservative-ci-gate — Staleness checking is designed as a safe CI gate: it never mutates state, only checks IN nodes, requires both source fields, and exits nonzero to fail the pipeline

Dependents

These beliefs depend on this one:

Details