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Training Assessments Data Quality Suite — Record Audit, String Normalisation & Exact Deduplication
x402
Training Assessments Data Quality Suite — Record Audit, String Normalisation & Exact Deduplication 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 local analytical reports on training assessment records (pre_score, post_score): a record quality audit, string normalisation, and exact row deduplication — up to 200 rows per call.
Price / call$0.01
Success—
StatusUnknown
How this service works
Training assessments — Record quality audit + String normalisation + Exact row deduplication: Record quality audit + String normalisation + Exact row deduplication for supplied training assessments records (pre_score, post_score). 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 highlighting missing, null, or out-of-range values in the training assessment rows; (2) a string normalisation report showing standardised versions of text fields like course_group; and (3) an exact row deduplication report identifying and removing fully identical rows — all computed locally against the supplied data, no external lookups.
Example use cases
Pre-analysis data cleaning for assessment scores
“Before I run my learning outcome analysis, can you audit these 80 training assessment rows for quality issues, normalise any messy string fields like course_group, and flag any exact duplicate records? Each row has a row_id, course_group, date, pre_score, and post_score.”
Deduplication check on imported LMS export
“I exported training records from our LMS and I suspect there are duplicate rows — can you run an exact row deduplication check plus a quality audit on this dataset of 120 assessment entries? Fields are row_id, course_group, date, pre_score, and post_score.”
String normalisation for course group labels
“Our course_group labels in the assessment data are inconsistently formatted — can you normalise the strings across these 60 training records and also give me a quality audit and deduplication report? Each record has row_id, course_group, date, pre_score, and post_score.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-education-11-191?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need three bundled data-quality operations (quality audit, string normalisation, exact deduplication) on training assessment records in a single low-cost call. It is best suited for pre-processing education or HR training data (pre_score/post_score) before downstream analysis, when you have up to 200 rows and want a quick, local, no-external-lookup quality pass without building custom cleaning pipelines.
Side effects
- More than 200 rows submitted — request rejected due to row limit
- Missing required fields (row_id, course_group, date, pre_score, or post_score) — validation error returned
- Date field not in YYYY-MM-DD format — pattern validation failure
- row_id is empty or exceeds 80 characters — schema rejection
- Empty rows array submitted — minItems constraint violation
- Payment of 0.01 USDC not completed — 402 Payment Required response
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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