# Render Jobs — Record Quality Audit + String Normalisation + Date by Category Pivot

> Render Jobs — Record Quality Audit + String Normalisation + 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).

Audits data quality, normalises strings, and produces a date-by-category pivot for up to 200 render job records (render_seconds, sample_count) in three bundled analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-creative-02-206?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/render-jobs-record-quality-audit-string-normalisation-date-by-cfa63bd9
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_Ky3cqB5GaOvwBbdbu_8o9

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 render-jobs-record-quality-audit-string-normalisation-date-by-cfa63bd9 -d '<json body>'
```

Example prompt: Can you audit these render job records for data quality issues, normalise the string fields, and give me a date-by-category pivot on render_seconds? I have up to 50 rows with row_id, asset_group, date, render_seconds, and sample_count.

## When to prefer this

Choose this endpoint when you have render job records (with render_seconds and/or sample_count) and need three bundled analytical operations — quality audit, string normalisation, and date-category pivot — in a single low-cost call (0.01 USDC). It is ideal for offline/batch data preparation, pre-ingestion QA, or pipeline reporting when no live lookups or external enrichment are needed and the dataset is ≤200 rows.

## Known failure modes

- Rows array empty or missing — returns validation error
- More than 200 rows submitted — rejected with maxItems error
- Invalid date format (not YYYY-MM-DD) — schema validation failure
- Numeric fields outside allowed range (±1,000,000,000,000) — rejected
- Missing required fields (row_id, asset_group, date) — schema error
- Invalid field enum value (not render_seconds or sample_count) — rejected

## How this service works

Render jobs — Record quality audit + String normalisation + Date by category pivot: Record quality audit + String normalisation + Date by category pivot for supplied render jobs records (render_seconds, sample_count). Up to 200 rows; 3 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 3 supplied-data reports for up to 200 rows.

## Output

Three bundled analytical reports: (1) a record quality audit flagging missing values, out-of-range numbers, or malformed dates; (2) a string normalisation report showing cleaned asset_group and row_id values; and (3) a date-by-category pivot table summarising the chosen numeric field (render_seconds or sample_count) broken down by date and asset group — all derived from the supplied rows, with no external lookups.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "rows": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "row_id",
     "asset_group",
     "date",
     "render_seconds",
     "sample_count"
    ],
    "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
     },
     "sample_count": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "render_seconds": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "asset_group": "group-a",
     "sample_count": 1,
     "render_seconds": 10
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "asset_group": "group-b",
     "sample_count": 2,
     "render_seconds": 20
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "asset_group": "group-a",
     "sample_count": 3,
     "render_seconds": 15
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "asset_group": "group-b",
     "sample_count": 4,
     "render_seconds": 30
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "render_seconds",
    "sample_count"
   ],
   "type": "string",
   "default": "render_seconds"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/render-jobs-record-quality-audit-string-normalisation-date-by-cfa63bd9/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)