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Record Routing Quality Audit, String Normalisation & Duplicate Key Report
x402
Record Routing Quality Audit, 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 2026-10-15).
Runs three local analytical reports (quality audit, string normalisation, and duplicate key detection) on up to 200 record routing rows containing accepted and rejected record counts.
Price / call$0.01
Success—
StatusUnknown
How this service works
Record routing — Record quality audit + String normalisation + Duplicate key report: Record quality audit + String normalisation + Duplicate key report 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
Three independent reports delivered for the submitted batch of up to 200 record routing rows: (1) a record quality audit flagging anomalies or data issues in the accepted_records and rejected_records fields, (2) a string normalisation report cleaning and standardising text fields such as dataset_group, and (3) a duplicate key report identifying any repeated row_id or dataset group combinations. All analysis is performed locally with no external lookups.
Example use cases
ETL pipeline data quality check
“I just ran my nightly ETL job and I want to audit the quality of the record routing output — can you check these 120 rows for quality issues, normalise any inconsistent group name strings, and flag any duplicate row IDs? The rows cover accepted and rejected record counts from 2026-11-01 through 2026-11-30.”
Duplicate key detection across dataset groups
“I suspect some of my routing records have duplicate row IDs across group-a and group-b datasets — can you run a duplicate key report on these 80 routing rows dated between 2026-09-01 and 2026-09-30 and let me know which ones are repeated?”
String normalisation before data merge
“Before I merge my record routing tables, I need the string values in the dataset_group field normalised for consistency — can you run the string normalisation report on these 60 rows of accepted and rejected record data so everything is standardised?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-19-192?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need to simultaneously run quality auditing, string normalisation, and duplicate key detection on record routing data (accepted/rejected record counts by dataset group and date) in a single cheap call. It is ideal for post-ETL validation pipelines, pre-merge data hygiene checks, or routine data quality monitoring on routing datasets of up to 200 rows. All processing is local and offline — do not use it when you need live external lookups, ML-based predictions, or professional data assessments.
Side effects
- Batch exceeds 200 rows — request will be rejected
- Missing required fields (row_id, date, accepted_records, rejected_records) cause row-level validation errors
- Invalid date format (not YYYY-MM-DD) causes parsing failure
- accepted_records or rejected_records values outside the allowed numeric range cause rejection
- Empty rows array returns an error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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