# Texture Baking Analytics — String Normalisation + Category Frequencies

> Texture Baking Analytics — String Normalisation + 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 2026-10-17).

Runs two local analytical reports on texture baking records: string normalisation of text fields and category frequency counts for asset groups, using up to 200 supplied rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-creative-10-024?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-17
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/texture-baking-analytics-string-normalisation-category-frequencies-faff2b17
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_m_YoGj_JMIiSMnxW14CDX

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-string-normalisation-category-frequencies-faff2b17 -d '<json body>'
```

Example prompt: Can you run string normalisation and category frequency analysis on my texture baking records? I have up to 50 rows with fields like row_id, asset_group, date, bake_seconds, and texture_pixels — here's the data.

## When to prefer this

Choose this endpoint when you have up to 200 texture baking records and need both string normalisation of categorical fields and a frequency breakdown of asset groups in a single low-cost call ($0.01 USDC). It is best for offline/batch analytical use where no live lookup, prediction, or external data enrichment is needed — purely local computation on supplied data.

## Known failure modes

- More than 200 rows supplied — request will be rejected or truncated
- Missing required fields (row_id, bake_seconds, texture_pixels) cause row-level errors
- Invalid date format (not YYYY-MM-DD) may cause parsing issues
- Null numeric values for bake_seconds or texture_pixels may be excluded from numeric summaries
- Empty or whitespace-only asset_group values may produce ambiguous category buckets

## How this service works

Texture baking — String normalisation + Category frequencies: String normalisation + 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) string-normalised versions of text fields (row_id, asset_group, date) in the supplied rows, and (2) category frequency counts showing how many records belong to each asset_group value — all 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-string-normalisation-category-frequencies-faff2b17/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)