# Texture Baking Analytics — Daily Sum Series + Date by Category Pivot

> Texture Baking Analytics — Daily Sum Series + 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 2026-10-21).

Computes two analytical reports (daily sum time series and date-by-category pivot table) from supplied texture baking records (bake_seconds, texture_pixels) for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-creative-10-143?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-21
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/texture-baking-analytics-daily-sum-series-date-by-category-pivot-2e163584
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_kFvMlGm_EbhKfqiPqHXun

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-daily-sum-series-date-by-category-pivot-2e163584 -d '<json body>'
```

Example prompt: Can you run a daily sum series and date-by-category pivot on these texture baking records? I have 4 rows with asset groups 'group-a' and 'group-b', dates from 2026-10-01 to 2026-10-04, and I want the analysis on bake_seconds.

## When to prefer this

Choose this endpoint when you have raw texture baking records (up to 200 rows) and need both a daily aggregated time series and a cross-tabulated category pivot in a single low-cost call. It is ideal for 3D pipeline analytics, render farm reporting, or asset group performance audits where you supply your own data and need fast offline computation without any external lookup or prediction.

## Known failure modes

- Fewer than 1 row supplied — minimum row count not met
- More than 200 rows supplied — exceeds maximum row count limit
- Invalid date format (not YYYY-MM-DD) — pattern validation failure
- Missing required fields (row_id, asset_group, date, bake_seconds, texture_pixels) on any row
- Invalid field enum value (must be 'bake_seconds' or 'texture_pixels')
- Payment of 0.01 USDC not completed — x402 payment required before response
- Numeric values outside allowed range (-1,000,000,000,000 to 1,000,000,000,000)

## How this service works

Texture baking — Daily sum series + Date by category pivot: Daily sum series + 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 daily sum time series showing total values of the selected field (bake_seconds or texture_pixels) aggregated per date, and (2) a date-by-category pivot table breaking down those totals by asset_group across dates. Both reports are derived entirely from the supplied input rows (up to 200) with no external data or predictions.

## 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-daily-sum-series-date-by-category-pivot-2e163584/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)