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Record Routing Analytics: Quality Audit + String Normalisation + Keyed Dataset Comparison
x402
Record Routing Analytics: Quality Audit + String Normalisation + Keyed Dataset Comparison 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 on record routing data — quality audit, string normalisation, and keyed dataset comparison — for up to 200 rows of accepted/rejected record counts.
Price / call$0.01
Success—
StatusUnknown
How this service works
Record routing — Record quality audit + String normalisation + Keyed dataset comparison: Record quality audit + String normalisation + Keyed dataset comparison for supplied record routing records (accepted_records, rejected_records). 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: (1) a record quality audit flagging data issues in the accepted/rejected record fields, (2) a string normalisation report cleaning and standardising text fields like dataset_group, and (3) a keyed dataset comparison report highlighting row-by-row differences between the primary and comparison dataset — all computed locally with no external lookups.
Example use cases
Pre-pipeline record routing data quality check
“Before we push this batch to production, can you audit the quality of our record routing data? I have up to 150 rows with accepted_records and rejected_records per dataset_group — I want to know if there are any quality issues I should fix first.”
Normalising group labels across routing datasets
“Our routing dataset has inconsistent string formatting in the dataset_group field across different rows. Can you run string normalisation on these 80 rows of record routing data so we get clean, consistent group names?”
Comparing current vs previous routing record batch
“I have two versions of our record routing data from this week and last week — same row IDs and dataset groups but different accepted_records and rejected_records counts. Can you do a keyed comparison to highlight what changed between the two batches?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-19-207?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need three simultaneous analytical passes — quality audit, string normalisation, and keyed dataset comparison — on record routing data (accepted/rejected record counts per group) in a single $0.01 call. Ideal for lightweight, offline data quality checks on batches up to 200 rows without any external API calls, predictions, or professional assessments. Prefer alternatives if you need live lookups, predictive analytics, or datasets larger than 200 rows.
Side effects
- More than 200 rows submitted — only up to 200 rows are supported per call
- Missing required fields (row_id, dataset_group, date, accepted_records, rejected_records) cause validation errors
- Date field not in YYYY-MM-DD format causes schema rejection
- Numeric values outside the allowed range (-1T to +1T) cause validation errors
- Empty rows array (minItems:1 not satisfied) causes rejection
- Comparison dataset (other) missing or mismatched row_ids may produce incomplete comparison report
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| other | array |
Tags
x402
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