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Numeric Precision Comparisons — Record Quality Audit, String Normalisation & Exact Row Deduplication
x402
Numeric Precision Comparisons — Record Quality Audit, String Normalisation & Exact Row Deduplication 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).
Runs three local analytical reports (record quality audit, string normalisation, and exact row deduplication) on up to 200 rows of numeric source-vs-transformed value pairs, with no external lookups or live data.
Price / call$0.01
Success—
StatusUnknown
How this service works
Numeric precision comparisons — Record quality audit + String normalisation + Exact row deduplication: Record quality audit + String normalisation + Exact row deduplication 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
Three independent analytical reports generated locally: (1) a record quality audit highlighting missing, null, or out-of-range values; (2) a string normalisation report for text fields like row_id and dataset_group; and (3) an exact row deduplication report identifying repeated records across the submitted rows. No external data is fetched.
Example use cases
ETL pipeline output validation
“I've run a numeric transformation pipeline and want to check the output quality — can you audit the records for quality issues, normalise any string fields, and flag exact duplicates? Here are my rows: row-1, group-a, 2026-10-01, source 100.5, transformed 100.499; row-2, group-b, 2026-10-02, source 200.0, transformed 199.998. Check up to 30 rows.”
Pre-analysis deduplication check
“Before I run my analysis, can you check this batch of 80 numeric records for exact duplicate rows and give me a deduplication report? Each row has a row_id, dataset_group, date, source_value, and transformed_value — I want to make sure there are no repeated entries sneaking in.”
Data migration accuracy audit
“We just migrated a numeric dataset and I need to verify the transformation accuracy. Can you run a full record quality audit comparing source_value to transformed_value for my 120 rows, and also tell me if any rows are exact duplicates? Groups are 'legacy' and 'migrated', dates from 2025-01-01 onward.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-20-191?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a combined, cost-efficient data quality pass over a batch of up to 200 numeric source-vs-transformed records — getting quality audit, string normalisation, and deduplication all in one call for $0.01 USDC. Prefer it over single-purpose tools when you want all three analytical reports in a single request without any external API calls or live lookups.
Side effects
- Exceeding 200 rows returns a validation error
- Rows missing required fields (row_id, dataset_group, date, source_value, transformed_value) are rejected
- Date fields not matching YYYY-MM-DD pattern cause schema validation failure
- Numeric values outside the range -1,000,000,000,000 to 1,000,000,000,000 are rejected
- Empty rows array returns an error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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