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Promotion Observations — String Normalisation + Duplicate Key Report
x402
Promotion Observations — String Normalisation + Duplicate Key Report 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).
Runs two local analytical reports on promotion observation records: string normalisation of text fields and a duplicate key detection report, covering up to 200 rows of discount_amount and units_sold data.
Price / call$0.01
Success—
StatusUnknown
How this service works
Promotion observations — String normalisation + Duplicate key report: String normalisation + Duplicate key report 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 independent analytical reports: (1) a string normalisation report showing standardised versions of text fields such as store_group, and (2) a duplicate key report identifying any rows sharing the same row_id, covering up to 200 supplied promotion observation rows with no external lookups or predictions.
Example use cases
Pre-analysis promotion data cleanup
“Before I analyze this month's promotion results, can you normalise the store_group strings and flag any duplicate row IDs in my dataset? I have 120 rows covering October 2026 with discount_amount and units_sold columns.”
Retail discount data audit
“I need to audit my promotion observations for data quality issues — specifically duplicate row keys and messy string values in store_group. Can you run both reports on my 80 rows of discount and units-sold records?”
Promotion dataset deduplication check
“We're merging two promotion datasets and I'm worried there are duplicate row IDs. Can you run a duplicate key report and string normalisation on the combined 150-row file that has store_group, date, discount_amount, and units_sold?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-retail-05-021?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need lightweight, local data-quality checks on promotion observation records — specifically string normalisation of categorical fields and duplicate key detection — without requiring external lookups, predictions, or professional assessments. Best suited for datasets up to 200 rows where both reports are needed together at low cost.
Side effects
- Exceeding 200 rows returns a validation error
- Missing required fields (row_id, store_group, date, discount_amount, units_sold) causes rejection
- Invalid date format (not YYYY-MM-DD) triggers schema validation failure
- Numeric values outside ±1,000,000,000,000 are rejected
- Empty rows array returns an error
- Payment of 0.01 USDC must be included or request is rejected
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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