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Brand Mention Inventories — Category Frequencies + IQR Outlier Flags
x402
Brand Mention Inventories — Category Frequencies + 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 2026-10-16).
Computes category frequencies and IQR-based outlier flags for brand mention inventory records (mention_count or source_count) across company groups, delivering two analytical reports for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Brand mention inventories — Category frequencies + IQR outlier flags: Category frequencies + IQR outlier flags 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) category frequency counts for each company_group in the submitted rows, and (2) IQR-based outlier flags identifying which rows have mention_count or source_count values that fall outside the interquartile range. Results are derived entirely from the supplied data with no external lookups.
Example use cases
Detecting spike days in brand mentions
“I have 120 rows of daily brand mention data for our top 5 company groups — can you run category frequencies and IQR outlier detection on the mention_count field so I can spot which days had abnormally high or low coverage?”
Source diversity audit for PR campaign
“We tracked brand mentions across 80 records with source_count and mention_count — run the category frequency and IQR outlier reports on source_count so I can see which company groups had unusually narrow or broad source spread.”
Weekly brand monitoring data QA
“Before I finalize this week's brand mention inventory report (about 150 rows, grouped by company_group), can you compute the category frequencies and flag any IQR outliers in mention_count so I can catch data quality issues?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-company-18-107?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have up to 200 rows of brand mention inventory data and need both a category frequency breakdown and IQR outlier detection in a single call. It is ideal for local, offline-style statistical analysis with no external data dependencies — suitable for QA passes, anomaly triage, or summarizing brand monitoring exports. Prefer it over general-purpose analytics tools when you want a structured two-report output (frequencies + outlier flags) specifically calibrated for mention_count and source_count fields.
Side effects
- Fewer than 1 row submitted — minimum row requirement not met
- More than 200 rows submitted — exceeds maximum batch size
- Missing required fields (row_id, company_group, date, mention_count, source_count) on any row — validation error
- Invalid date format (not YYYY-MM-DD) — pattern mismatch rejection
- Field selector not one of 'mention_count' or 'source_count' — enum validation failure
- Numeric values outside allowed range (±1,000,000,000,000) — schema rejection
- Payment not provided or insufficient — x402 payment required
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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