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Damaged Stock Base-100 Series + Keyed Dataset Comparison
x402
Damaged Stock Base-100 Series + Keyed Dataset Comparison 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 two local analytical reports on supplied damaged stock records: a Base-100 index series and a keyed dataset comparison across up to 200 rows.
Price / call$0.01
Success—
StatusUnknown
How this service works
Damaged stock — Base-100 series + Keyed dataset comparison: Base-100 series + Keyed dataset comparison 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
Returns two analytical reports computed locally: (1) a Base-100 index series that normalizes the selected field over time or across rows, and (2) a keyed dataset comparison that aligns and contrasts the primary rows dataset against the other dataset by row_id, store_group, and date — covering up to 200 rows total with no external lookups or predictions.
Example use cases
Seasonal damage rate benchmarking
“I have two sets of damaged stock records for our warehouse groups — one from Q1 and one from Q2, about 80 rows each. Can you run a base-100 index series and keyed comparison on them using damaged_units so I can see how damage rates shifted between quarters?”
Store group damage performance comparison
“Compare these two damaged stock datasets for store groups A and B across the last 30 days — use handled_units as the field. I need both the base-100 indexed series and the keyed dataset comparison side by side.”
Damage trend normalization for reporting
“I need to normalize our damaged_units data to a base-100 index and compare it against our target baseline dataset — here are both datasets with around 120 rows each. Can you generate both the index series report and the keyed comparison?”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-retail-18-168?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need offline, self-contained analytical computation on damaged stock records without any external data lookup, prediction, or third-party assessment. It is ideal when you have two comparable datasets and need both a normalized Base-100 trend series and a direct keyed row-by-row comparison in a single low-cost call. Prefer it over general analytics platforms when data privacy matters (no external transmission of row data) and when your input is already structured with row_id, store_group, date, handled_units, and damaged_units.
Side effects
- Exceeds 200-row limit — request rejected or truncated
- Missing required fields (row_id, store_group, date, handled_units, damaged_units) — validation error
- Date format not matching YYYY-MM-DD pattern — schema validation failure
- Mismatched row keys between primary and comparison datasets — comparison may return partial results
- Null values in the selected field — may produce incomplete index series
- Invalid field enum value — request rejected
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| other | array | |
| base_index | integer |
Tags
x402
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