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Dataset Storage Record Quality Audit, String Normalisation & Duplicate Key Report
x402
Dataset Storage Record 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 on supplied dataset storage records (used_mb, row_count): record quality audit, string normalisation, and duplicate key detection — up to 200 rows, no external lookups.
Price / call$0.01
Success—
StatusUnknown
How this service works
Dataset storage — Record quality audit + String normalisation + Duplicate key report: Record quality audit + String normalisation + Duplicate key report for supplied dataset storage records (used_mb, row_count). 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 used_mb and row_count fields; (2) a string normalisation report highlighting inconsistencies or format issues in string fields like row_id and dataset_group; and (3) a duplicate key report identifying any repeated row_id or key combinations across the supplied rows.
Example use cases
Storage usage data integrity check
“I have about 150 rows of storage usage records with fields for row_id, dataset_group, date, used_mb, and row_count — can you audit their quality, normalise the string fields, and flag any duplicate row IDs for me?”
Duplicate dataset group key detection
“Before I merge these dataset storage records into our main table, can you run a duplicate key report and quality audit on them? There are around 80 rows with used_mb and row_count values that I want checked.”
Pre-pipeline string normalisation
“I need to clean up the dataset_group and row_id strings in my storage records before ingestion — can you run the string normalisation report plus the quality audit on these 60 rows so I know what needs fixing?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-18-192?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a quick, low-cost ($0.01 USDC) batch of three complementary data-quality reports on dataset storage records without making any external API calls or live lookups. It is ideal for pre-ingestion validation pipelines, ad-hoc data audits, or automated quality gates on storage usage datasets of up to 200 rows. Prefer it over general-purpose data quality tools when your records specifically track used_mb and row_count storage metrics organised by dataset_group.
Side effects
- Rows array exceeds 200 items — request will be rejected
- Missing required fields (row_id, dataset_group, date, used_mb, row_count) in any row — validation error
- Date field not matching YYYY-MM-DD pattern — schema validation failure
- Empty rows array (minItems: 1 not met) — rejected
- Numeric fields outside allowed range — schema rejection
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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