# Texture Baking Data — Exact Row Deduplication + Date by Category Pivot

> Texture Baking Data — Exact Row Deduplication + 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 2026-10-17).

Deduplicates texture baking records and generates a date-by-category pivot table for a selected numeric field, returning two analytical reports from supplied data.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-creative-10-052?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-data-exact-row-deduplication-date-by-category-pivot-7b45e998
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_aW0TQ_Geq4lJ602bcCtjU

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-data-exact-row-deduplication-date-by-category-pivot-7b45e998 -d '<json body>'
```

Example prompt: I have up to 200 rows of texture baking records with row_id, asset_group, date, bake_seconds, and texture_pixels — can you run exact row deduplication and a date-by-category pivot on bake_seconds and give me both reports?

## When to prefer this

Choose this endpoint when you have a batch of up to 200 texture baking records (with bake_seconds and texture_pixels fields) and need both exact row deduplication and a date-by-asset-group pivot in a single low-cost call. It is ideal for 3D/VFX pipeline data QA workflows where duplicate entries are common and cross-date category summaries are needed. Prefer it over general-purpose data tools when the domain is specifically texture baking and you want two packaged reports for $0.01 USDC without setting up custom analytics infrastructure.

## Known failure modes

- Input array is empty or exceeds 200 rows — validation error
- Missing required fields (row_id, asset_group, date, bake_seconds, texture_pixels) on any row — schema rejection
- Date field does not match YYYY-MM-DD pattern — validation error
- Selected field enum value is not 'bake_seconds' or 'texture_pixels' — rejection
- Numeric fields outside allowed range (-1,000,000,000,000 to 1,000,000,000,000) — validation error
- Payment of 0.01 USDC not provided or rejected — HTTP 402 error

## How this service works

Texture baking — Exact row deduplication + Date by category pivot: Exact row deduplication + 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) an exact row deduplication report identifying and removing fully duplicate rows from the supplied texture baking dataset, and (2) a date-by-category pivot table summarizing the selected numeric field (bake_seconds or texture_pixels) broken down by date and asset_group — all 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-data-exact-row-deduplication-date-by-category-pivot-7b45e998/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)