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Account Research Coverage Daily Sum Series with IQR Outlier Flags
x402
Account Research Coverage Daily Sum Series with IQR Outlier Flags is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-19).
Computes daily sum time series and IQR-based outlier flags for account research coverage metrics (researched_accounts and target_accounts) from supplied row data.
Price / call$0.01
Success—
StatusUnknown
How this service works
Account research coverage — Daily sum series + IQR outlier flags: Daily sum series + IQR outlier flags for supplied account research coverage records (researched_accounts, target_accounts). 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 daily sum time series showing aggregated values of the selected metric (researched_accounts or target_accounts) grouped by date, and (2) IQR-based outlier flags identifying which dates have statistically anomalous values. Both reports are computed locally from the supplied data with no external lookups.
Example use cases
Sales team research activity audit
“I have 150 rows of daily account research logs with company_group, date, researched_accounts, and target_accounts — can you compute the daily totals and flag any days where researched_accounts looks like a statistical outlier using IQR?”
Spotting data entry errors in coverage records
“We've been logging target_accounts daily across two company groups for the past quarter and I suspect some dates have bad entries — can you run the daily sum series and IQR outlier flags on this dataset to surface any suspicious values?”
Comparing research intensity across groups over time
“I want to understand how our researched_accounts volume trends day by day across group-a and group-b — please aggregate the daily sums and highlight any outlier days so I know where to investigate further.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-company-08-140?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both a daily time series aggregation and IQR-based outlier detection for account research coverage data in a single low-cost call. It is ideal when you have up to 200 rows of pre-collected data with researched_accounts or target_accounts metrics grouped by company and date, and you want purely local statistical analysis without any external data enrichment, prediction, or live lookup.
Side effects
- Missing required fields (row_id, date, company_group) returns a validation error
- Date strings not matching YYYY-MM-DD pattern are rejected
- Exceeding 200 rows causes the request to fail with a row limit error
- Numeric values outside ±1,000,000,000,000 are rejected
- Empty rows array returns an error
- Invalid field enum value (not researched_accounts or target_accounts) causes failure
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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