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Numeric Precision Comparisons — Record Quality Audit + Exact Row Deduplication + Adjacent Row Changes
x402
Numeric Precision Comparisons — Record Quality Audit + Exact Row Deduplication + Adjacent Row Changes is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-15).
Analyzes up to 200 rows of source_value/transformed_value numeric pairs, producing three independent local reports: a record quality audit, exact row deduplication, and adjacent row change detection.
Price / call$0.01
Success—
StatusUnknown
How this service works
Numeric precision comparisons — Record quality audit + Exact row deduplication + Adjacent row changes: Record quality audit + Exact row deduplication + Adjacent row changes for supplied numeric precision comparisons records (source_value, transformed_value). 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 three independent analytical reports for the submitted rows: (1) a record quality audit flagging nulls, out-of-range values, and completeness issues; (2) an exact row deduplication report identifying identical records; and (3) an adjacent row change report showing value differences between consecutive rows — all computed locally without external lookups.
Example use cases
ETL pipeline numeric validation
“I just ran an ETL job and want to check the output for data quality issues — can you audit up to 200 rows of my source_value vs transformed_value pairs, flag any duplicates, and show me where adjacent row values changed? Here's the dataset grouped by pipeline stage.”
Deduplication before data warehouse load
“Before I load these records into the warehouse, can you check for exact duplicate rows in this dataset of up to 150 numeric precision comparison records, and also give me a quality audit and adjacent change report on the source_value field?”
Time-series transformation drift detection
“I have a daily numeric series with source and transformed values from 2026-10-01 through 2026-10-30 across two dataset groups. Can you run all three reports — quality audit, exact row deduplication, and adjacent row changes — on the transformed_value field so I can spot any drift or anomalies?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-20-217?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need all three data quality operations — record audit, deduplication, and adjacent change detection — in a single call for up to 200 rows of numeric source/transformed value pairs. It is ideal for ETL validation, data pipeline QA, and numeric transformation auditing where no external data lookup or ML prediction is needed and cost efficiency matters ($0.01 for three reports).
Side effects
- Input array exceeds 200 rows — request will be rejected
- Missing required fields (row_id, dataset_group, date, source_value, transformed_value) cause validation errors
- Date strings not matching YYYY-MM-DD pattern are rejected
- Numeric values outside [-1,000,000,000,000, 1,000,000,000,000] range are rejected
- Empty rows array returns an error
- Invalid field enum value (must be source_value or transformed_value) causes rejection
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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