# Texture Baking Analytics — Numeric Distribution + Date by Category Pivot

> Texture Baking Analytics — Numeric Distribution + 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 2026-10-27).

Computes a numeric distribution report and a date-by-category pivot table for up to 200 texture baking records (bake_seconds or texture_pixels fields).

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-creative-10-083?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-27
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/texture-baking-analytics-numeric-distribution-date-by-category-pivot-3a976daa
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_Q3mSet0PNzgHd4f9KLnsW

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 texture-baking-analytics-numeric-distribution-date-by-category-pivot-3a976daa -d '<json body>'
```

Example prompt: Can you run a numeric distribution and date-by-category pivot on these texture baking records — analyzing bake_seconds — for my four asset groups across October 2026? I have up to 200 rows with row IDs, asset_group labels, dates, bake_seconds, and texture_pixels values.

## When to prefer this

Choose this endpoint when you have texture baking records and need both a numeric distribution and a date-by-category pivot in a single call at low cost ($0.01 USDC for both reports). It is ideal for 3D rendering pipeline analytics, creative asset QA, or production reporting where data is already collected and you need fast offline statistical summaries without external lookups or predictions.

## Known failure modes

- Rows array is empty or missing — minimum 1 row required
- More than 200 rows submitted — maxItems limit exceeded
- Invalid date format in any row — must match YYYY-MM-DD pattern
- Null values in bake_seconds or texture_pixels may affect distribution accuracy
- Invalid field selector — must be either 'bake_seconds' or 'texture_pixels'
- Missing required row fields (row_id, asset_group, date, bake_seconds, texture_pixels) causes schema validation failure

## How this service works

Texture baking — Numeric distribution + Date by category pivot: Numeric distribution + Date by category pivot for supplied texture baking records (bake_seconds, texture_pixels). 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: (1) a numeric distribution of the selected field (bake_seconds or texture_pixels) showing spread, frequency, and statistical breakdown; and (2) a date-by-category pivot table grouping values by asset_group and date. Both reports are derived from the supplied rows using local analytical engines — no external data is fetched.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/texture-baking-analytics-numeric-distribution-date-by-category-pivot-3a976daa/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)