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Duplicate Observations String Normalisation and Adjacent Row Changes Analyser
x402
Duplicate Observations String Normalisation and Adjacent Row Changes Analyser 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).
Analyses supplied duplicate-observation records to produce two local analytical reports: string normalisation and adjacent row changes, for up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Duplicate observations — String normalisation + Adjacent row changes: String normalisation + Adjacent row changes 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 analytical reports generated locally from the supplied data: (1) a string normalisation report identifying inconsistencies or variations in string fields across the duplicate observation records, and (2) an adjacent row changes report showing how the selected numeric field (duplicate_rows or total_rows) changes between consecutive rows. No external lookups or predictions are made.
Example use cases
Data pipeline duplicate quality check
“I have daily pipeline metrics for three dataset groups over the past week — can you run a string normalisation and adjacent row changes report on the duplicate_rows counts so I can spot any sudden spikes or label inconsistencies?”
Comparing duplicate rates across groups
“Here's a table of duplicate_rows and total_rows readings for groups alpha, beta, and gamma across 10 dates — run both the string normalisation and adjacent row changes analyses so I can see how duplicates shift between consecutive days per group.”
Pre-migration data quality audit
“Before we migrate our database, I want to check for string inconsistencies in the dataset group names and sudden jumps in duplicate row counts — can you analyse these 50 rows using the duplicate observations reporter, focusing on the total_rows field?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-04-029?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need lightweight, offline analytical reports on duplicate observation data — specifically string normalisation across group labels and adjacent row change detection for a numeric field — without requiring any external data source, live lookup, or ML prediction. Ideal for data quality checks on small-to-medium batches (up to 200 rows) at very low cost ($0.01 USDC for both reports).
Side effects
- Fewer than 1 row supplied — request rejected
- More than 200 rows supplied — exceeds maximum batch limit
- Invalid date format (not YYYY-MM-DD) — validation error
- Missing required fields (row_id, dataset_group, date, duplicate_rows, total_rows) — schema validation failure
- Numeric values outside allowed range — validation error
- Invalid field selector (not 'duplicate_rows' or 'total_rows') — enum validation error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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