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Promotion Observations — Duplicate Key Report + Category Frequencies
x402
Promotion Observations — Duplicate Key Report + Category Frequencies is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-23).
Analyzes up to 200 promotion observation records (discount_amount, units_sold) to produce a duplicate row_id report and category frequency counts for store_group and date fields.
Price / call$0.01
Success—
StatusUnknown
How this service works
Promotion observations — Duplicate key report + Category frequencies: Duplicate key report + Category frequencies for supplied promotion observations records (discount_amount, units_sold). 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) a duplicate key report identifying any row_ids that appear more than once in the submitted dataset, and (2) category frequency tables showing how often each distinct value of store_group and date appears across the supplied promotion observation rows. Both reports are computed locally from the submitted data with no external lookups.
Example use cases
Retail promotion data quality audit
“I have 150 promotion observation records from our retail stores — each has a row_id, store_group, date, discount_amount, and units_sold. Can you run a duplicate key check on row_id and also tell me how frequently each store_group and date appears in the dataset?”
Pre-analysis deduplication for discount data
“Before I run any analysis on our promotion dataset, I want to know if there are any duplicate row IDs that could skew results, and I also want a breakdown of how many records fall under each store group. The data has discount_amount and units_sold columns along with dates.”
Store group distribution check for promotions
“We ran promotions across several store groups last quarter and I want to see if the data is evenly distributed — can you count how many promotion records we have per store group and date, and flag any duplicate row IDs in our dataset of about 80 rows?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-retail-05-057?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need to simultaneously detect duplicate row IDs and compute category frequency distributions on promotion data (discount_amount, units_sold) in a single low-cost call. It is ideal for lightweight data quality audits on small-to-medium promotion datasets (up to 200 rows) without requiring a full analytics platform. It does not perform predictions, live lookups, or external data enrichment — it works purely on the data you supply.
Side effects
- Fewer than 1 row submitted — request rejected due to minItems constraint
- More than 200 rows submitted — request rejected due to maxItems limit
- row_id missing or empty string — validation error
- date field does not match YYYY-MM-DD pattern — validation error
- discount_amount or units_sold outside allowed numeric range — validation error
- Malformed JSON payload — HTTP 400 or similar parse error
- Payment of 0.01 USDC not completed — request blocked by x402 payment requirement
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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