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Shift Coverage Audit — Record Quality + String Normalisation + Numeric Row Ordering
x402
Shift Coverage Audit — Record Quality + String Normalisation + Numeric Row Ordering is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-11-02).
Audits shift coverage records for quality issues, normalises team/date strings, and orders rows numerically across up to 200 supplied rows in three independent reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Shift coverage — Record quality audit + String normalisation + Numeric row ordering: Record quality audit + String normalisation + Numeric row ordering for supplied shift coverage records (covered_hours, required_hours). 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: (1) a record quality audit flagging malformed, missing, or out-of-range values in the shift rows; (2) a string normalisation report on fields like team_group and date; (3) a numeric row ordering report ranking rows by the selected field (covered_hours or required_hours). No external lookups or predictions are made; all analysis is performed locally on the supplied data.
Example use cases
Pre-import shift data validation
“Before I load this week's shift schedule into our HR system, can you audit these 40 shift coverage rows for data quality issues, normalise the team_group names, and rank them by covered_hours so I can spot gaps?”
Weekly coverage gap detection
“I have shift records for our nursing teams from the past month — around 150 rows — can you run a record quality audit and numeric ordering on required_hours so I can see which shifts are furthest from being covered?”
Team scheduling data clean-up
“Our scheduling export has messy team names and some null hours values across about 80 rows — can you audit the data quality, normalise the string fields, and sort everything by covered_hours so I get three clean reports back?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-operations-15-196?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you have raw shift coverage records (up to 200 rows) and need three simultaneous local analytical operations — quality auditing, string normalisation, and numeric ordering — bundled into one low-cost call. It is ideal for pre-pipeline data cleaning of workforce scheduling exports where no live data lookup, ML prediction, or external system integration is required. Prefer alternatives if you need forecasting, real-time shift availability checks, or more than 200 rows processed at once.
Side effects
- Exceeding 200 rows returns a validation error
- Missing required fields (row_id, date, covered_hours, required_hours) causes a schema rejection
- Invalid date format (non-YYYY-MM-DD) triggers a pattern validation failure
- Supplying an unsupported field enum value (not covered_hours or required_hours) causes an error
- Empty rows array (minItems:1 violation) returns a schema error
- Payment not included or insufficient causes x402 payment-required rejection
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string |
Tags
x402
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