Skip to content

Reference

If you arrived here directly, the role pages curate which handbooks each role uses day-to-day.

Per-app structural reference — what each sheet shows, which dataset backs it, which filters and drills are wired, and which L1 invariants each row represents.

The intended user is the operator looking up "what does column X on sheet Y mean" or the integrator validating that their L2 instance produces the rows the dashboard expects.

Pages

  • L1 Reconciliation Dashboard — surfaces L1 invariant violations from any L2 instance:
    • Drift
    • Overdraft
    • Limit Breach
    • Stuck Pending
    • Stuck Unbundled
    • Supersession Audit
  • L2 Flow Tracing — Rails, Chains, Transfer Templates, and L2 hygiene exceptions for the integrator validating their L2 instance against the SPEC.
  • Investigation — recipient fanout, volume anomalies, money-trail provenance, and account-network graphs for the compliance / AML triage team.
  • Install — which PyPI extras to pick for your use case (emit-only / deploy / demo DB / audit PDF / docs build / full dev environment).
  • ETL — Data Integration — for the engineer populating the two base tables from upstream systems.
  • Customization — for the developer dropping the dashboards onto their own backend, brand, and AWS account.
  • Domain Model (SPEC) — the canonical L1 / L2 / L3 layer model: primitives, derivatives, system constraints, and the L2 institutional vocabulary every shipped app reads.
  • Schema v6 — Data Feed Contract — column specs + metadata key catalog + ETL examples for the two base tables.
  • L1 Invariants — the formal SHOULD-violation matview definitions that every L1 dashboard sheet rolls up.