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Inventory Administration — Base-100 Series + Secondary-Measure Weighted Mean
x402
Inventory Administration — Base-100 Series + Secondary-Measure Weighted Mean is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-24).
Computes a Base-100 index series and a secondary-measure weighted mean for inventory administration records (count_sessions, discrepancy_count) over up to 200 rows using local analytical engines.
Price / call$0.01
Success—
StatusUnknown
How this service works
Inventory administration — Base-100 series + Secondary-measure weighted mean: Base-100 series + Secondary-measure weighted mean for supplied inventory administration records (count_sessions, discrepancy_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 analytical reports for the supplied inventory rows: (1) a Base-100 index series normalizing the chosen field (count_sessions or discrepancy_count) relative to the specified base row, and (2) a secondary-measure weighted mean across all rows. Results are computed locally without external lookups or predictions, covering up to 200 input rows.
Example use cases
Inventory session trend indexing
“I have 3 months of daily inventory session counts across two warehouse teams — can you normalize the count_sessions to a base-100 series starting from the first row and also compute the weighted mean, so I can compare how each group's volume has changed?”
Discrepancy rate baseline analysis
“Can you run a base-100 index on my discrepancy_count data across 80 inventory audit rows, using row 5 as the base, and also give me the weighted mean for discrepancy_count? I want to see how discrepancies have shifted relative to that reference point.”
Multi-team inventory operations report
“I've got 120 rows of inventory administration records split across four team groups with dates, count_sessions, and discrepancy_count — generate a base-100 series and a secondary-measure weighted mean report on count_sessions using row index 0 as the baseline.”
Technical details
Endpoint
POSThttps://market.datapackvibe.com/x402/assistant-ib26-operations-21-166?utm_source=zero.xyzWhen to prefer
Choose this endpoint when you need both a Base-100 normalization series and a weighted mean computed together on inventory administration data (count_sessions or discrepancy_count) in a single $0.01 call. It is best suited for offline, batch-style statistical analysis of up to 200 rows without requiring external data lookups, predictions, or real-time feeds. Prefer it over general-purpose analytics tools when cost efficiency and pre-packaged dual-report output on inventory metrics are the priority.
Side effects
- More than 200 rows submitted — request rejected due to maxItems constraint
- Invalid date format (not YYYY-MM-DD) causes schema validation failure
- Missing required fields (row_id, date, count_sessions, discrepancy_count) returns validation error
- base_index out of range (>= number of rows) may produce undefined reference behavior
- Null values in count_sessions or discrepancy_count may affect weighted mean computation
- Invalid field enum value (not count_sessions or discrepancy_count) causes rejection
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rows | array | |
| field | string | |
| base_index | integer |
Tags
x402
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