# Texture Baking Analytics — Category Frequencies + Two-Measure Correlation

> Texture Baking Analytics — Category Frequencies + Two-Measure Correlation is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-31).

Computes category frequency counts and Pearson/Spearman correlation between bake_seconds and texture_pixels for up to 200 supplied texture baking records.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-creative-10-108?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-31
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/texture-baking-analytics-category-frequencies-two-measure-correlation-a65940fb
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_6QEl0lQ8OE12EmczRwxVF

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-two-measure-correlation-a65940fb -d '<json body>'
```

Example prompt: Analyze my texture baking records and give me two reports: how often each asset group appears, and the correlation between bake_seconds and texture_pixels. Here are my rows: row-1 (group-a, 2026-10-01, 120 seconds, 4096 pixels), row-2 (group-b, 2026-10-02, 240 seconds, 8192 pixels), row-3 (group-a, 2026-10-03, 90 seconds, 2048 pixels).

## When to prefer this

Choose this endpoint when you have tabular texture baking records with categorical grouping and two numeric measures, and you need both a frequency distribution and a correlation statistic in a single cheap call ($0.01 USDC). It is self-contained (no external data sources) and deterministic, making it ideal for repeatable pipeline QA, batch audits, or exploratory analysis of asset baking logs without needing a full analytics platform.

## Known failure modes

- Input array exceeds 200 rows — request will be rejected or truncated
- Missing required fields (row_id, bake_seconds, texture_pixels) cause row-level errors
- Null values in bake_seconds or texture_pixels may reduce correlation sample size
- Date strings not matching YYYY-MM-DD pattern will fail schema validation
- Sending fewer than 2 rows may produce degenerate or undefined correlation results

## How this service works

Texture baking — Category frequencies + Two-measure correlation: Category frequencies + Two-measure correlation 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 category frequency table showing how many records belong to each asset_group value, and (2) a two-measure correlation report quantifying the statistical relationship between bake_seconds and texture_pixels across the supplied rows. Both reports are computed locally from the supplied 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
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/texture-baking-analytics-category-frequencies-two-measure-correlation-a65940fb/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)