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Duplicate Observations — String Normalisation + Duplicate Key Report
x402
Duplicate 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 2026-10-20).
Runs two local analytical reports on supplied duplicate-observation records: string normalisation and duplicate key detection, for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Duplicate observations — String normalisation + Duplicate key report: String normalisation + Duplicate key report for supplied duplicate observations records (duplicate_rows, total_rows). 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 for the supplied rows: (1) a string normalisation report showing standardised string values across the dataset groups, and (2) a duplicate key report identifying key collisions or duplicate entries within the supplied observation records. Both reports are generated locally from the supplied data with no external lookups.
Example use cases
Audit ETL pipeline duplicate keys
“I ran an ETL job and suspect there are duplicate keys across my dataset groups — can you run a duplicate key report on these 8 rows? Each row has a row_id, a group name like 'sales' or 'returns', a date between 2026-09-01 and 2026-09-08, and duplicate_rows/total_rows counts I'll supply.”
Normalise strings in observation batch
“My team ingested survey observation records with inconsistent string formatting across dataset groups. Can you run string normalisation on these 50 rows so I can see what's been standardised, along with a duplicate key check? I'll provide the row_ids, groups, dates, and duplicate counts.”
Data quality check before warehouse merge
“Before I merge two datasets into our warehouse, I need to check for duplicate keys and normalise string fields. Can you analyse these 120 observation rows — each has a row_id, a dataset_group, a date in YYYY-MM-DD format, and duplicate_rows versus total_rows — and give me both reports?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-04-021?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both string normalisation and duplicate key detection on a single batch of up to 200 observation rows at low cost ($0.01 USDC for both reports). It is ideal for offline/local analytical audits where no live lookups or external data enrichment are needed, and when you want two complementary data quality reports in a single call. If you only need deduplication or only need string normalisation as separate operations, consider sibling endpoints.
Side effects
- Exceeding 200 rows causes request rejection
- Missing required fields (row_id, dataset_group, date, duplicate_rows, total_rows) result in validation errors
- Dates not matching YYYY-MM-DD pattern fail schema validation
- Numeric values outside allowed range cause rejection
- Empty rows array fails minItems constraint
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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