Asteria Fleet Dq Audit

Asteria Fleet Data Quality Hub — Audit & Certification

When to use

A task that:

• Points at the "Asteria Fleet Data Quality Hub" at a <TASK_ENV_BASE_URL>,
• Stages payloads/case_scope.json (scope) and payloads/answer_template.json (output contract), and
• Asks you to audit / reconcile / certify a collection and return one JSON object.

Inputs (read in this order — read every payload fully)

1. prompt.txt — the business ask and which hub interfaces are relevant.
2. payloads/case_scope.json — collection_id, cutoff / as_of, canonical units, base currency, focus IDs, decision-panel IDs, ranking policy, certification thresholds / gate, status→action map.
3. payloads/answer_template.json — the output contract: required keys, enums, minItems/maxItems, regex patterns, ordering descriptions, numeric precision. This is law.
4. environment_access.md — base URL, auth token, allowed endpoints. The ONLY source for network access; never invent endpoints or credentials.

The answer_template is the single source of truth for output shape. case_scope supplies the variable inputs (which IDs, which thresholds, which ranking policy).

Procedure (8 phases)

A. Load & internalize inputs

Read all four inputs. Extract: collection_id, cutoff/as_of, canonical units, base currency, every focus/decision-panel ID list, the ranking sort policy, certification thresholds + status→action map, and the full output contract (every required key, enum, count, ordering, and precision rule).

B. Connect & catalog (see reference/hub_access.md)

Using environment_access.md:

• GET /api/catalog/collections — confirm the collection exists; note its family & source_systems.
• GET /api/catalog/schema — list the queryable views and their fields.
• GET /api/source-snapshots?collection=<collection_id> — list snapshots; pick the authoritative one (snapshot_status = CERTIFIED, matching the business cutoff). Its snapshot_id is reported as authoritative_snapshot_id.

C. Pull all rows + reference data (paginate fully)

Collections are larger than one page — page through completely (limit/offset for GETs; LIMIT/OFFSET in SQL; honor the truncated flag). Pull domain rows plus the reference views: aliases, unit conversions, FX rates. See reference/data_and_reconciliation.md for the view per domain. Never sample.

D. Reconcile & audit (see reference/data_and_reconciliation.md)

• Resolve overlapping source records by the authoritative snapshot (every row carries a snapshot_id).
• Detect cross-snapshot logical duplicates; retain the authoritative occurrence.
• Detect expected-vs-recognized class/category mismatches via the alias map.
• Detect unrecognized (0 canonical) and ambiguous (>1 canonical) aliases → quarantine / unrecognized.
• Detect invalid quantities (nonpositive/invalid volume, weight, distance, odometer; invalid/missing timestamp; invalid labor) → quarantine or invalid_event.
• Normalize units to the canonical unit via conversions; convert currency to USD via FX.
• Compute normalized totals excluding quarantined items. Valid class mismatches stay in totals.

E. Focus rollups & rankings

Compute the focus-area rollups (focus assets / people / clusters) and the ranking arrays. Follow the case_scope sort policy exactly (primary sort DESC + tie-breaks; rank ascending). See reference/domain_map.md for per-domain focus/ranking.

F. Infer opaque control codes (see reference/domain_map.md)

For every public ID in the case_scope decision panels, infer the applicable internal control code from the shared records + the reconciled audit. Code expansions are intentionally NOT in the task materials. Use ONLY the enum values the answer_template allows. One row per scoped ID, sorted by ID ascending.

G. Certification / release decision

Apply case_scope thresholds + status→action map (or certification_gate):

• status ∈ {PASS, PASS_WITH_EXCEPTIONS, HOLD} → action ∈ {RELEASE, REVIEW_EXCEPTIONS, BLOCK_AND_REMEDIATE}.
• e.g. quarantine_rate ≤ pass_max_quarantine_rate → PASS; ≤ pass_with_exceptions_max_quarantine_rate → PASS_WITH_EXCEPTIONS; else HOLD.

H. Assemble & validate output (see reference/output_contract.md)

Build exactly one JSON object matching answer_template, then validate before emitting:

• All required keys present; no extra keys (additionalProperties:false at every level).
• Every enum value contract-allowed; every array within minItems/maxItems.
• Every ID list deduplicated and sorted per the contract.
• Numeric precision exact (2 dp for measures & USD; 4 dp for rates; counts are integers).
• Count partitions sum correctly; every case_scope decision-panel ID appears in the output. Emit the JSON object only — no commentary, no Markdown.

Core rules (always)

• The answer_template is the contract. When the contract and your intuition conflict, the contract wins.
• One JSON object. No commentary. No Markdown. No extra keys.
• Read environment_access.md for all network access; never hardcode credentials or invent endpoints.
• Page through all rows; never sample a collection.
• Authoritative snapshot (CERTIFIED) resolves overlaps; quarantined items never enter normalized totals; valid mismatches do.
• Infer control codes from evidence; never guess outside the contract's enum.
• Validate against the template before emitting.

Reference files

• reference/hub_access.md — base URL/auth, endpoint list, GET pagination, /api/query SQL DSL, response shapes.
• reference/data_and_reconciliation.md — the 8 views, reference-data semantics, snapshots, reconcile/audit/normalize rules, certification math.
• reference/output_contract.md — ordering, precision, enums, partition integrity, and a pre-emit self-check.
• reference/domain_map.md — the known collection families (fuel, freight, maintenance, contacts) → endpoints, views, control-code families, focus/ranking, contract shape, and the code-inference method.