# Inventory Counts Date-by-Category Pivot

> Inventory Counts Date-by-Category Pivot is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-19).

Pivots inventory count records by date and warehouse category, summarizing book_units or counted_units across up to 200 rows into a cross-tabulated matrix.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-sector-analytics-inventory-counts-pivot?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-19
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/inventory-counts-date-by-category-pivot-3f6cf4ab
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_rwq0rV_coVOTvMrlxsUv_

Status and success rate cover calls made through Zero and Zero's own probes. Third-party monitors may report differently.

## How to call it through Zero

Zero handles the 402 payment challenge and records the run. With the Zero CLI installed (`npm i -g @zeroxyz/cli`):

```sh
zero fetch --capability inventory-counts-date-by-category-pivot-3f6cf4ab -d '<json body>'
```

Example prompt: Take these inventory count records for our two warehouses — group-a and group-b — across October 2026 and produce a date-by-warehouse pivot table showing book_units for each date.

## When to prefer this

Choose this endpoint when you have structured inventory count records (with dates, warehouse labels, and unit counts) and need a cross-tabulated pivot view for auditing, reporting, or comparison — especially when you want a lightweight, deterministic local computation without calling a full BI platform or data warehouse. Ideal for up to 200 records where no external enrichment or forecasting is needed.

## Known failure modes

- Fewer than 1 row supplied — validation error
- More than 200 rows submitted — request rejected at schema level
- Invalid date format (not YYYY-MM-DD) — row-level or request-level error
- Missing required fields (row_id, warehouse, date) — schema validation failure
- All numeric values null — pivot may return empty or zero-filled cells
- Duplicate row_ids — may cause unexpected aggregation behavior

## How this service works

Inventory counts - Date by category pivot: Date by category pivot for Inventory counts. Up to 200 supplied typed records. Local numeric and data-quality processing; no external enrichment or forecasting. One of 25 profiles or calculations across 20 shared operations in this sector. 0.01 USDC includes one bounded date by category pivot deliverable.

## Output

A date-by-category pivot table (cross-tabulation matrix) where rows represent dates and columns represent warehouse categories, with cells containing aggregated values of the selected field (book_units or counted_units). Derived locally from the supplied records with no external data enrichment.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "rows": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "row_id",
     "warehouse",
     "date",
     "book_units",
     "counted_units"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "maxLength": 10
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "warehouse": {
      "type": "string",
      "default": "",
      "maxLength": 80
     },
     "book_units": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "counted_units": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "warehouse": "group-a",
     "book_units": 10,
     "counted_units": 1
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "warehouse": "group-b",
     "book_units": 20,
     "counted_units": 2
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "warehouse": "group-a",
     "book_units": 15,
     "counted_units": 3
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "warehouse": "group-b",
     "book_units": 30,
     "counted_units": 4
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "book_units",
    "counted_units"
   ],
   "type": "string",
   "default": "book_units"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/inventory-counts-date-by-category-pivot-3f6cf4ab/health.json
- [Zero catalog index](https://www.zero.xyz/llms.txt)
- [Other services from market.datapackvibe.com](https://www.zero.xyz/host/market.datapackvibe.com/llms.txt)