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Brand Mention Inventories — Record Quality Audit + Exact Row Deduplication + Numeric Row Ordering
x402
Brand Mention Inventories — Record Quality Audit + Exact Row Deduplication + Numeric Row Ordering 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).
Audits record quality, deduplicates exact rows, and applies numeric ordering to brand mention inventory data (mention_count, source_count) across up to 200 rows, returning 3 independent analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Brand mention inventories — Record quality audit + Exact row deduplication + Numeric row ordering: Record quality audit + Exact row deduplication + Numeric row ordering for supplied brand mention inventories records (mention_count, source_count). Up to 200 rows; 3 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 3 supplied-data reports for up to 200 rows.
Output
Returns 3 independent analytical reports: (1) a record quality audit flagging data issues in the supplied rows, (2) an exact row deduplication report identifying and removing identical records, and (3) a numeric row ordering report sorting rows by the selected numeric field (mention_count or source_count). All processing is local with no external lookups. Up to 200 input rows supported.
Example use cases
Weekly brand mention data cleanup
“I have a week's worth of brand mention records across several company groups and I need you to audit them for quality issues, remove any exact duplicate rows, and sort them numerically by mention_count — here's the dataset with row IDs, dates, mention counts, and source counts for up to 80 rows.”
Pre-report deduplication for marketing team
“Before I send this brand mention inventory to the marketing team, can you run a record quality audit, deduplicate any exact matching rows, and apply numeric ordering on the source_count field? I'll paste in the rows with company_group, date, and counts.”
Validating scraped mention data integrity
“I just scraped brand mention data from our monitoring tool and it might have duplicates and quality issues — can you run all 3 reports (quality audit, exact deduplication, and numeric row ordering) on these mention_count records so I can see what's clean and what needs fixing?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-company-18-213?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have brand mention inventory data (with mention_count and source_count fields) that needs simultaneous quality auditing, exact deduplication, and numeric ordering in a single low-cost call. Ideal for pre-processing pipelines before dashboarding or reporting. Best when your dataset fits within 200 rows and you need all 3 reports at once rather than separate analytical services.
Side effects
- Input array exceeds 200 rows — request will be rejected
- Missing required fields (row_id, company_group, date, mention_count, source_count) cause row-level validation errors
- Malformed date strings not matching YYYY-MM-DD pattern rejected
- Numeric values outside ±1,000,000,000,000 range flagged
- Empty rows array (minItems:1 violated) returns error
- Invalid field enum value (not mention_count or source_count) causes rejection
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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