# Lighting Setups — Record Quality Audit + String Normalisation + Date by Category Pivot

> Lighting Setups — 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 2026-10-22).

Runs three local analytical reports on lighting setup records: a record quality audit, string normalisation, and a date-by-category pivot, for up to 200 rows of light_count and render_seconds data.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-creative-11-206?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-22
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/lighting-setups-record-quality-audit-string-normalisation-date-by-cdc988cd
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_PhbWpUGY0bkqFyRCbx-bC

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 lighting-setups-record-quality-audit-string-normalisation-date-by-cdc988cd -d '<json body>'
```

Example prompt: Can you run a record quality audit, string normalisation, and date-by-category pivot on my lighting setup data? I have up to 50 rows with fields row_id, asset_group, date, light_count, and render_seconds — use light_count as the field for analysis.

## When to prefer this

Choose this endpoint when you need three bundled analytical operations — quality audit, string normalisation, and date pivot — on lighting setup records in a single cost-efficient call ($0.01 USDC for all three reports). Ideal for pre-processing or QA steps in 3D rendering pipelines where you want to validate, clean, and summarise up to 200 rows of lighting data without any external lookups or live data dependencies.

## Known failure modes

- More than 200 rows submitted — exceeds maxItems limit
- Missing required fields (row_id, asset_group, date, light_count, or render_seconds) causes validation error
- Malformed date string not matching YYYY-MM-DD pattern rejected
- Invalid field enum value (must be light_count or render_seconds)
- Empty rows array (minItems: 1) returns error
- Numeric values outside allowed range cause schema rejection

## How this service works

Lighting setups — Record quality audit + String normalisation + Date by category pivot: Record quality audit + String normalisation + Date by category pivot for supplied lighting setups records (light_count, render_seconds). 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

Returns three independent analytical reports: (1) a record quality audit flagging completeness and validity issues per row, (2) a string normalisation report cleaning and standardising text fields like asset_group, and (3) a date-by-category pivot summarising the selected numeric field (light_count or render_seconds) broken down by date and asset group — all computed locally from the supplied data, no external lookups.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/lighting-setups-record-quality-audit-string-normalisation-date-by-cdc988cd/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)