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Brand Mention Inventories — Exact Row Deduplication + IQR Outlier Flags
x402
Brand Mention Inventories — Exact Row Deduplication + 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).
Deduplicates exact rows and flags IQR-based outliers in supplied brand mention inventory records (mention_count, source_count) for up to 200 rows across 2 reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Brand mention inventories — Exact row deduplication + IQR outlier flags: Exact row deduplication + 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
Returns two analytical reports: (1) an exact row deduplication report identifying and removing fully duplicate records from the input dataset, and (2) an IQR-based outlier flag report marking records whose mention_count (or source_count) values fall outside the interquartile range boundaries. Up to 200 input rows are processed using local analytical engines with no external lookups.
Example use cases
Brand mention data quality audit
“I have 150 rows of brand mention inventory data for companies across November 2025 — each row has a row_id, company_group, date, mention_count, and source_count. Can you deduplicate exact rows and flag any IQR-based outliers in mention_count so I know which records are anomalies?”
Source count anomaly detection for PR team
“Our PR team scraped brand mention data for 80 records across Q3 2025. Can you run exact deduplication and IQR outlier flagging on source_count to help us spot which brand-date combinations have unusually high or low source counts?”
Weekly brand inventory cleanup pipeline
“Every Monday we get a fresh batch of brand mention records — about 200 rows with company_group, date, mention_count, and source_count fields. Can you deduplicate the exact duplicate rows and flag IQR outliers on mention_count so we can send a clean dataset downstream?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-company-18-049?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need lightweight, local statistical data quality checks on brand mention inventory records — specifically exact deduplication combined with IQR outlier detection on mention_count or source_count fields — without requiring external lookups, ML models, or live data sources. Best suited for batch sizes up to 200 rows where the cost of $0.01 USDC for two simultaneous reports is acceptable.
Side effects
- Input array exceeds 200 rows — request will be rejected
- Missing required fields (row_id, company_group, date, mention_count, source_count) cause validation failure
- Invalid date format (must match YYYY-MM-DD) results in schema rejection
- Numeric values outside ±1,000,000,000,000 bounds cause validation errors
- Empty input array (minItems: 1 not met) returns error
- Insufficient row variance for IQR computation with very small datasets
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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