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Dataset Storage Record Quality Audit + Equal-Width Histogram
x402
Dataset Storage Record Quality Audit + Equal-Width Histogram 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 a record quality audit and equal-width histogram analysis on up to 200 dataset storage records (used_mb or row_count), returning two independent analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Dataset storage — Record quality audit + Equal-width histogram: Record quality audit + Equal-width histogram 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 reports: (1) a record quality audit flagging missing values, nulls, out-of-range entries, and other data issues per row; and (2) an equal-width histogram showing frequency distribution of the chosen field (used_mb or row_count) across the specified number of bins. Both reports are computed locally with no external lookups.
Example use cases
Storage usage distribution analysis
“I have 120 dataset storage records from the past quarter — each with a row_id, group name, date, used_mb, and row_count. Can you run a histogram with 10 bins on the used_mb field and also flag any quality issues in the records?”
Row count data quality pre-check
“Before I load these dataset records into our pipeline, can you do a quality audit on the row_count field and show me a 5-bin equal-width histogram so I can spot any weird outliers or missing values? I have about 80 rows with group and date info.”
Multi-group storage profiling
“I've got records for two dataset groups — 'warehouse-prod' and 'warehouse-dev' — spanning 6 months, around 150 rows total. Can you audit the data quality and generate an equal-width histogram with 12 bins for used_mb so I can compare the distributions?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-analytics-18-013?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both a data quality audit and a frequency distribution histogram for dataset storage records (used_mb or row_count) in a single call. It is ideal for pre-pipeline data validation, exploratory profiling of storage usage, or detecting anomalies across up to 200 rows. Prefer it over generic statistical APIs when your data has the specific dataset storage schema (row_id, dataset_group, date, used_mb, row_count) and you need two bundled analytical reports at low cost.
Side effects
- Exceeding 200 rows returns a validation error
- Missing required fields (row_id, dataset_group, date, used_mb, row_count) causes schema validation failure
- Invalid date format (not YYYY-MM-DD) triggers a pattern validation error
- bins value outside 1–30 range is rejected
- Submitting an empty rows array is rejected (minItems: 1)
- Non-numeric values for used_mb or row_count when null is not acceptable may cause computation errors
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| bins | integer | |
| rows | array | |
| field | string |
Tags
x402
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