# Texture Baking Analytics — Numeric Distribution & Category Frequencies

> Texture Baking Analytics — Numeric Distribution & Category Frequencies 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 numeric distribution statistics and category frequency breakdowns for texture baking records (bake_seconds and texture_pixels fields) from up to 200 supplied rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-creative-10-072?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-category-frequencies-1bd2c349
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_F7ueeVowxSo8UL8d9OUGc

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-category-frequencies-1bd2c349 -d '<json body>'
```

Example prompt: Can you analyze the distribution of bake_seconds and the asset_group frequencies in my texture baking records? Here are my rows: row-1 on 2026-10-01 for group-a with 120 bake_seconds and 4096 texture_pixels, row-2 on 2026-10-02 for group-b with 240 bake_seconds and 8192 texture_pixels, row-3 on 2026-10-03 for group-a with 180 bake_seconds and 4096 texture_pixels.

## When to prefer this

Choose this endpoint when you have up to 200 texture baking records and need both a numeric distribution report and a category frequency breakdown in a single low-cost call ($0.01 USDC). It is ideal for 3D rendering pipelines, game asset audits, or any workflow where bake_seconds and texture_pixels metrics need statistical profiling without external data access or prediction. Prefer it over general-purpose analytics APIs when your data fits the specific texture baking schema and you want two reports bundled together cheaply.

## Known failure modes

- More than 200 rows submitted — endpoint rejects input exceeding maxItems limit
- Missing required fields (row_id, bake_seconds, texture_pixels, date, asset_group) causes validation error
- Malformed date format (not YYYY-MM-DD) triggers pattern validation failure
- Null numeric values may reduce distribution accuracy if prevalent
- Invalid field enum value (not 'bake_seconds' or 'texture_pixels') causes rejection
- Empty rows array rejected due to minItems:1 constraint

## How this service works

Texture baking — Numeric distribution + Category frequencies: Numeric distribution + Category frequencies 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

Two analytical reports: (1) a numeric distribution summary for the chosen field (bake_seconds or texture_pixels), including statistics like min, max, mean, percentiles, and histogram bins; and (2) a category frequency table showing how often each asset_group value appears across the supplied rows. Both reports are computed locally from the provided 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-numeric-distribution-category-frequencies-1bd2c349/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)