# Lighting Setups Data Quality & Analytics — Audit, Normalisation & Grouped Summary

> Lighting Setups Data Quality & Analytics — Audit, Normalisation & Grouped Summary is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-21).

Runs three local analytical reports on lighting setup records: record quality audit, string normalisation, and grouped numeric summary for light_count and render_seconds fields.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-creative-11-194?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-21
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/lighting-setups-data-quality-analytics-audit-normalisation-grouped-111b5f7b
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_AUnvOA7lnBFw2XXj6UDb7

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-data-quality-analytics-audit-normalisation-grouped-111b5f7b -d '<json body>'
```

Example prompt: Can you run a quality audit, string normalisation, and grouped numeric summary on my lighting setup records? I have rows with asset_group, date, light_count, and render_seconds — here are up to 50 rows, and I want the summary grouped by light_count.

## When to prefer this

Choose this endpoint when you need a combined data quality audit, string normalisation, and grouped statistical summary for lighting setup or 3D render records in a single low-cost call. It is ideal for creative/VFX pipeline data hygiene checks on batches up to 200 rows, where no external lookup or prediction is needed and all computation is local. It is not suitable for real-time monitoring, ML prediction, or datasets exceeding 200 rows.

## Known failure modes

- Exceeding 200 rows returns a validation error
- Missing required fields (row_id, asset_group, date, light_count, render_seconds) causes row-level errors
- Invalid date format (not YYYY-MM-DD) fails schema validation
- Numeric values outside ±1,000,000,000,000 are rejected
- Empty rows array is rejected
- Invalid field enum value causes request failure

## How this service works

Lighting setups — Record quality audit + String normalisation + Grouped numeric summary: Record quality audit + String normalisation + Grouped numeric summary 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 reports: (1) a record quality audit flagging missing, malformed, or out-of-range values; (2) normalised/standardised string representations of string fields like asset_group; and (3) a grouped numeric summary (e.g. mean, min, max, count) for the selected numeric field (light_count or render_seconds) broken out by asset_group. All computed locally with 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-data-quality-analytics-audit-normalisation-grouped-111b5f7b/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)