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Damaged Stock Quality Audit + Equal-Width Histogram
x402
Damaged Stock 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 2026-10-25).
Runs a data quality audit and equal-width histogram analysis on up to 200 damaged stock records (handled_units or damaged_units) and returns two independent analytical reports.
Price / call$0.01
Success—
StatusUnknown
How this service works
Damaged stock — Record quality audit + Equal-width histogram: Record quality audit + Equal-width histogram for supplied damaged stock records (handled_units, damaged_units). 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
Two independent reports: (1) a record quality audit identifying data issues such as nulls, out-of-range values, or malformed entries across the supplied rows; and (2) an equal-width histogram showing bin edges and counts for the selected field (handled_units or damaged_units) using the specified number of bins (1–30). No external lookups or predictions are performed — all analysis is local and deterministic.
Example use cases
Retail damage log quality check
“I have 150 rows of damaged stock records from my warehouse — each row has a date, store group, handled units, and damaged units. Can you run a data quality audit on them and also produce a 10-bin equal-width histogram on the damaged_units field so I can see the distribution?”
Distribution analysis for inventory reporting
“Before I send my monthly inventory report, can you check the data quality of my handled_units records across all 80 store entries and generate a 5-bin histogram on handled_units to flag any weird distribution patterns?”
Spot-check damage rates across store groups
“I've got 60 damaged stock rows from three store groups over the past quarter. Run a quality audit to catch any nulls or bad values, and give me an equal-width histogram with 8 bins on damaged_units so I can see where most damage is clustering.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-retail-18-013?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need a combined data quality audit and distribution histogram for damaged stock records in a single low-cost call, and your dataset is 200 rows or fewer. It is ideal for retail or warehouse analysts who want to validate record completeness and understand the shape of handled or damaged unit distributions before reporting or downstream processing. It does not perform live lookups, forecasting, or external integrations.
Side effects
- More than 200 rows submitted — request rejected
- Invalid date format (not YYYY-MM-DD) — validation error
- Missing required fields (row_id, handled_units, damaged_units) — schema error
- Bins parameter out of range (must be 1–30) — validation error
- Empty rows array — request rejected
- Payment of 0.01 USDC not completed — 402 response
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| bins | integer | |
| rows | array | |
| field | string |
Tags
x402
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