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Aggregation Checks — Trailing Mean Series + Secondary-Measure Weighted Mean
x402
Aggregation Checks — Trailing Mean Series + Secondary-Measure Weighted Mean is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-15).
Computes a rolling trailing mean series and a secondary-measure weighted mean for user-supplied aggregation check records containing source_sum and aggregate_sum fields.
Price / call$0.01
Success—
StatusUnknown
How this service works
Aggregation checks — Trailing mean series + Secondary-measure weighted mean: Trailing mean series + Secondary-measure weighted mean for supplied aggregation checks records (source_sum, aggregate_sum). Up to 200 rows; 2 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 2 supplied-data reports for up to 200 rows.
Output
Returns two independent analytical reports: (1) a trailing mean series computed over the specified rolling window for the chosen field (source_sum or aggregate_sum), and (2) a secondary-measure weighted mean across the supplied rows. Results cover up to 200 rows of user-supplied aggregation check data and are generated locally without external lookups or live data fetches.
Example use cases
Finance reconciliation trailing mean check
“I need to audit my monthly source vs aggregate sums for reconciliation — can you run a trailing mean series with a window of 5 and a weighted mean on these 80 rows of aggregation check data grouped by department?”
Supply chain aggregation quality analysis
“I have 120 rows of supplier aggregation records with source_sum and aggregate_sum columns across different dataset groups from 2026-09 through 2026-12 — run both the trailing mean series and secondary-measure weighted mean with a window of 4 targeting aggregate_sum.”
Data pipeline aggregate drift detection
“Can you compute a rolling trailing mean and weighted mean on my pipeline aggregation check output — 30 rows with source_sum and aggregate_sum per date, window of 2, so I can spot drift between raw source totals and aggregated figures?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-17-151?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need dual statistical reports — a rolling trailing mean series and a weighted mean — on pre-supplied aggregation check data (source_sum vs aggregate_sum) without any external data lookup. Ideal for data reconciliation workflows, pipeline quality audits, and supply aggregation checks where you already have the rows locally and need lightweight batch computation at low cost ($0.01 USDC for two reports on up to 200 rows).
Side effects
- Missing required fields (row_id, date, dataset_group, source_sum, aggregate_sum) causes validation error
- Exceeding 200 rows returns an error or truncation
- Window size outside the range 2–200 causes rejection
- Malformed date strings not matching YYYY-MM-DD pattern cause parsing errors
- Null values in both source_sum and aggregate_sum may produce undefined weighted mean output
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| window | integer |
Tags
x402
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