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Brand Mention Inventories — Trailing Mean Series + Adjacent Row Changes
x402
Brand Mention Inventories — Trailing Mean Series + Adjacent Row Changes is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-16).
Computes trailing moving-average series and adjacent-row delta changes for brand mention inventory data (mention_count or source_count) across up to 200 rows, returning two analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Brand mention inventories — Trailing mean series + Adjacent row changes: Trailing mean series + Adjacent row changes for supplied brand mention inventories records (mention_count, source_count). 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
Two analytical reports: (1) a trailing mean series showing the rolling average of the selected field (mention_count or source_count) over the specified window size, and (2) an adjacent row changes report showing the difference between consecutive row values — both computed locally against the supplied dataset of up to 200 rows.
Example use cases
Brand buzz trend smoothing
“I have weekly brand mention data for three competitors over the past quarter — can you compute a trailing mean series with a window of 4 on mention_count to smooth out the noise and also show me the week-over-week deltas?”
Source diversity shift detection
“Run trailing mean and adjacent row change analysis on my source_count data for brand group 'techbrand-x' across 30 daily rows, using a window of 3, so I can see if our source diversity is trending up or down.”
Multi-group mention inventory audit
“I've got 120 rows of brand mention inventory records split across 5 company groups — analyze the mention_count field with a trailing window of 7 and give me both the smoothed series and the row-by-row changes for each group.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-company-18-146?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have brand mention inventory data already in hand and need fast, local computation of rolling averages and period-over-period deltas without any external data lookup, prediction, or enrichment. Ideal for agents that batch-process brand monitoring records and need two complementary analytical views (smoothed trend + raw delta) in a single low-cost call.
Side effects
- Missing required row fields (row_id, date, company_group) returns a validation error
- Window size larger than number of rows may produce partial or empty trailing mean results
- Rows exceeding 200-item limit are rejected
- Malformed date strings not matching YYYY-MM-DD pattern cause validation failure
- Null values in the selected metric field may produce gaps in the mean series
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| window | integer |
Tags
x402
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