fleet-data-quality-reconciliation

name

fleet-data-quality-reconciliation

description

Reconcile Asteria-style fleet data-quality hub collections into schema-valid audit JSON. Use when a task provides a prompt, case scope, answer contract/template, and read-only hub access for contact rosters, fuel or freight ledgers, maintenance histories, duplicate resolution, source-snapshot reconciliation, alias classification, unit/FX normalization, readiness counts, quarantine sets, ranked exception panels, or compact internal control-code panels.

Fleet Data Quality Reconciliation

Core Workflow

1. Read the prompt, case scope, and answer contract before querying data. Extract the collection ID, cutoff, business period, scoped stable IDs, required sort orders, numeric precision, allowed enum values, and whether totals include or exclude exceptions.
2. Inspect catalog/schema and source snapshots for the scoped collection. Treat snapshot business cutoffs and statuses as source-selection evidence; do not filter source rows by ingestion time unless the task explicitly says to.
3. Pull all in-scope rows through the read-only data interface. Use structured queries over paginated endpoint sampling when the collection may exceed one page.
4. Build a reproducible reconciliation table with raw rows, retained logical records, normalized fields, exception flags, and reason flags. Derive every output field from that table.
5. Validate the final object against the answer contract: exact top-level keys, no extra commentary, sorted arrays, unique IDs, integer counts, required enums, and stated rounding.

Source Resolution

• Prefer certified snapshots over provisional snapshots when the same stable public ID appears more than once. Keep provisional-only logical records unless the prompt says to certify only an authoritative snapshot.
• Count raw_row_count from in-scope raw rows, logical_*_count from retained stable IDs, and duplicate raw count as raw rows minus retained logical records when duplicates are defined by the stable ID.
• For duplicate-group outputs, include every stable ID with multiple raw occurrences, sorted by the public ID. Report all contributing snapshot IDs sorted lexicographically and the retained snapshot.