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Training Compliance Data Quality Suite: Record Audit + String Normalisation + Duplicate Key Report
x402
Training Compliance Data Quality Suite: Record 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 2026-10-26).
Runs three independent data-quality reports (record quality audit, string normalisation, and duplicate key detection) on up to 200 training compliance rows containing completed_courses and assigned_courses fields.
Price / call$0.01
Success—
StatusUnknown
How this service works
Training compliance — Record quality audit + String normalisation + Duplicate key report: Record quality audit + String normalisation + Duplicate key report for supplied training compliance records (completed_courses, assigned_courses). 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 missing, null, or out-of-range values in the submitted rows; (2) a string normalisation report showing standardised versions of text fields like team_group; and (3) a duplicate key report identifying any row_id values that appear more than once across the up to 200 submitted rows.
Example use cases
Pre-reporting HR data clean-up
“Before I submit our quarterly training compliance report, can you audit these 120 rows of course completion data for record quality issues, normalise the team group names, and check for any duplicate row IDs? The dataset has row_id, team_group, date, assigned_courses, and completed_courses columns.”
Detecting duplicate entries in LMS export
“I exported training records from our LMS and I suspect there are duplicate entries. Can you run the duplicate key report and record quality audit on these 85 rows so I can see which row_ids appear more than once and whether any records have missing or malformed fields?”
Standardising team labels across course data
“Our training data has inconsistent team_group labels like 'Sales', 'sales ', and 'SALES' mixed in. Can you run string normalisation plus a full record quality audit on these 200 compliance rows so I get a clean, consistent dataset with completed_courses and assigned_courses intact?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-operations-10-192?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need to validate, normalise, and deduplicate training compliance data (specifically completed_courses and assigned_courses records) in a single low-cost call without any external lookups or live HR system access. It is ideal for pre-processing LMS exports or HR data extracts before downstream reporting, when you need all three quality checks bundled for $0.01 rather than calling separate services.
Side effects
- Submitting more than 200 rows returns a validation error
- Missing required fields (row_id, date, completed_courses, assigned_courses) causes row-level audit failures
- Dates not matching YYYY-MM-DD pattern may be flagged in the record quality audit
- Empty row array (minItems:1 violated) returns an input validation error
- Numeric values outside ±1,000,000,000,000 range are rejected by schema validation
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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