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Dataset Storage — Record Quality Audit + Duplicate Key Report
x402
Dataset Storage — Record Quality Audit + 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 2026-10-21).
Runs two local analytical reports on supplied dataset storage records: a record quality audit and a duplicate key detection report, covering up to 200 rows of used_mb and row_count data.
Price / call$0.01
Success—
StatusUnknown
How this service works
Dataset storage — Record quality audit + Duplicate key report: Record quality audit + Duplicate key report for supplied dataset storage records (used_mb, row_count). 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 record quality audit identifying issues such as null values, out-of-range figures, or malformed fields in used_mb and row_count columns; and (2) a duplicate key report identifying any rows sharing the same key fields (e.g. row_id or dataset_group+date combinations). No external lookups are performed — all analysis is local.
Example use cases
Catch duplicate rows before ETL pipeline
“Before I run my ETL pipeline, can you check these 120 dataset storage records for duplicate row_ids and flag any quality issues in the used_mb and row_count columns? Here's the data with row_id, dataset_group, date, used_mb, and row_count fields.”
Monthly storage data integrity check
“I need to audit my monthly dataset storage report — I have 80 rows with dataset_group, date, used_mb, and row_count. Can you run a record quality audit and tell me if there are any duplicate keys or data problems?”
Validate migrated dataset records
“We just migrated our storage records to a new system and I want to verify the data landed correctly. Can you run a quality audit and duplicate key check on these 200 rows? Each row has a row_id, dataset_group, date, used_mb, and row_count.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-18-003?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need fast, offline (no external lookup) quality and deduplication analysis for dataset storage records specifically containing used_mb and row_count metrics. It is especially useful as a pre-pipeline validation step or post-migration integrity check. Prefer this over generic data quality tools when your records conform to the row_id/dataset_group/date/used_mb/row_count schema and you need both quality and duplicate reports in a single cheap call.
Side effects
- Rows array is empty or missing — validation error returned
- Row count exceeds 200 — request rejected with limit error
- Required fields (row_id, dataset_group, date, used_mb, row_count) missing from one or more rows — schema validation failure
- Date field does not match YYYY-MM-DD pattern — rejected
- row_id or dataset_group string exceeds 80 characters — rejected
- Numeric fields outside allowed range — schema rejection
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array |
Tags
x402
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