# Texture Baking Analytics — Category Frequencies + Daily Sum Series

> Texture Baking Analytics — Category Frequencies + Daily Sum Series 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).

Analyzes texture baking records to produce category frequency distributions and daily sum time-series reports for bake_seconds or texture_pixels fields.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-creative-10-102?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-category-frequencies-daily-sum-series-2aebd86d
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_I_U6hW2zRy2GGdEysTjLs

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-category-frequencies-daily-sum-series-2aebd86d -d '<json body>'
```

Example prompt: I have a batch of texture baking records with asset groups like 'environment' and 'character', dates, bake_seconds, and texture_pixels — can you run a category frequency breakdown and a daily sum series on the bake_seconds field for up to 200 rows?

## When to prefer this

Choose this endpoint when you have texture baking pipeline data (with asset groups, dates, and numeric bake metrics) and need both a categorical frequency breakdown and a daily aggregated time series in a single low-cost call. It is ideal for 3D rendering or game asset pipelines where you want to audit workload distribution and track output trends without external data dependencies. Prefer it over general-purpose analytics when your data conforms to the bake_seconds/texture_pixels schema.

## Known failure modes

- Missing required fields (row_id, date, asset_group, bake_seconds, texture_pixels) cause validation errors
- Date values not matching YYYY-MM-DD pattern are rejected
- Submitting more than 200 rows exceeds the row limit
- Null numeric values for the selected field may result in incomplete daily sums
- Empty rows array is rejected (minItems: 1)
- Invalid field enum value (not 'bake_seconds' or 'texture_pixels') causes schema error

## How this service works

Texture baking — Category frequencies + Daily sum series: Category frequencies + Daily sum series 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 category frequency table showing how often each asset_group value appears in the submitted rows, and (2) a daily sum time-series aggregating the chosen numeric field (bake_seconds or texture_pixels) by date. Both reports are computed locally from the submitted data with no external lookups.

## 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-category-frequencies-daily-sum-series-2aebd86d/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)