# Texture Baking Data Quality Audit with Adjacent Row Change Detection

> Texture Baking Data Quality Audit with Adjacent Row Change Detection 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).

Runs two local analytical reports on texture baking records: a record quality audit and an adjacent row change analysis, for up to 200 rows of bake_seconds or texture_pixels data.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-creative-10-011?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-data-quality-audit-with-adjacent-row-change-detection-0f232930
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_2Ha4J4R8Yc2mfzpqqMpzr

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-quality-audit-with-adjacent-row-change-detection-0f232930 -d '<json body>'
```

Example prompt: Can you run a record quality audit and adjacent row change report on these texture baking logs — I have up to 50 rows with bake_seconds and texture_pixels fields and I want to check the bake_seconds column for data issues and sequential changes?

## When to prefer this

Choose this endpoint when you need two combined analytical reports — record quality audit plus adjacent row change detection — on texture baking data (bake_seconds or texture_pixels) in a single low-cost call. Ideal for creative/3D asset pipelines where you want to validate data completeness and detect sequential anomalies without external lookups or live data connections. Best when your dataset is 200 rows or fewer and you want both reports bundled at $0.01 USDC.

## Known failure modes

- Fewer than 1 row submitted returns a validation error
- More than 200 rows submitted exceeds the per-call limit
- Invalid date format (not YYYY-MM-DD) causes schema rejection
- Missing required fields (row_id, asset_group, date, bake_seconds, texture_pixels) causes row-level errors
- Invalid field enum value (not bake_seconds or texture_pixels) rejected by schema
- Null numeric values may reduce completeness of change-detection report

## How this service works

Texture baking — Record quality audit + Adjacent row changes: Record quality audit + Adjacent row changes 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 independent analytical reports generated locally from the supplied data: (1) a record quality audit identifying missing, null, or anomalous values in the specified field across all submitted rows, and (2) an adjacent row change report highlighting value differences between consecutive rows for the selected metric (bake_seconds or texture_pixels), covering up to 200 rows per call.

## 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-quality-audit-with-adjacent-row-change-detection-0f232930/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)