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Record Routing Analytics: String Normalisation + Date by Category Pivot
x402
Record Routing Analytics: String Normalisation + Date by Category Pivot is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-24).
Performs string normalisation and date-by-category pivot analysis on supplied record routing data (accepted_records, rejected_records) for up to 200 rows, returning two independent analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Record routing — String normalisation + Date by category pivot: String normalisation + Date by category pivot for supplied record routing records (accepted_records, rejected_records). 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 independent analytical reports: (1) a string normalisation report cleaning and standardising text fields in the supplied routing records, and (2) a date-by-category pivot table summarising the selected metric (accepted_records or rejected_records) broken down by date and dataset_group — all computed locally from the supplied data with no external lookups.
Example use cases
ETL pipeline data quality review
“I have my ETL pipeline's record routing logs for last month — each row has a date, a dataset group, and counts of accepted and rejected records. Can you normalize the strings and pivot accepted_records by date and category so I can see which groups had the most failures?”
Rejected records trend by group
“Here's my record routing dataset with about 80 rows — row IDs, dates, dataset groups, and accepted and rejected record counts. Run the string normalisation and date-by-category pivot on the rejected_records field so I can spot which groups are consistently producing rejections.”
Multi-group routing acceptance audit
“I want to audit our routing acceptance rates across four dataset groups over Q3. I've got 120 rows with dates, group names, accepted_records, and rejected_records. Please normalise the strings and give me a pivot of accepted_records broken down by date and category.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-19-035?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have up to 200 rows of record routing data with accepted/rejected record counts grouped by category and date, and you need both string normalisation and a date-by-category pivot in a single low-cost call ($0.01 USDC). It is ideal for lightweight, local analytical processing of ETL or data pipeline quality metrics without requiring external data sources, live lookups, or prediction services.
Side effects
- Input array exceeds 200 rows — request will be rejected or truncated
- Missing required fields (row_id, date, accepted_records, rejected_records) — validation error
- Date field not in YYYY-MM-DD format — schema validation failure
- Numeric values outside allowed range (-1e12 to 1e12) — validation error
- Empty rows array — minimum 1 item required
- Invalid field selector not in enum [accepted_records, rejected_records] — validation error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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