# Scene Geometry — String Normalisation + Grouped Numeric Summary

> Scene Geometry — String Normalisation + Grouped Numeric Summary is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-17).

Normalises string fields and produces grouped numeric summary statistics (count, min, max, mean, etc.) for scene geometry records containing object_count and triangle_count fields, delivering two analytical reports for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-creative-05-023?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/scene-geometry-string-normalisation-grouped-numeric-summary-0e15ea90
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_31s-b4-EEu2g0MJTaNOs7

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 scene-geometry-string-normalisation-grouped-numeric-summary-0e15ea90 -d '<json body>'
```

Example prompt: I have a batch of 3D scene geometry records with asset groups like 'environment' and 'props', each with object_count and triangle_count values — can you normalise the string fields and give me a grouped numeric summary for object_count across up to 150 rows?

## When to prefer this

Choose this endpoint when you have scene geometry tabular data (up to 200 rows) with object_count and/or triangle_count fields and need both string normalisation of categorical labels and grouped descriptive statistics in a single cheap call ($0.01 USDC for two reports). Ideal for 3D asset pipelines, game development workflows, or animation studios that need lightweight local analytics without any external data fetch or prediction.

## Known failure modes

- Exceeding 200 rows returns a validation error
- Missing required fields (row_id, asset_group, date, object_count, triangle_count) causes a schema rejection
- Invalid date format (not YYYY-MM-DD) triggers a pattern validation error
- Null values in numeric fields may affect summary statistics output
- Selecting an invalid field enum value returns an error

## How this service works

Scene geometry — String normalisation + Grouped numeric summary: String normalisation + Grouped numeric summary for supplied scene geometry records (object_count, triangle_count). 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

Two analytical reports: (1) normalised string values for the asset_group and related text fields, and (2) grouped numeric summary statistics (e.g. count, min, max, mean, sum) for the selected numeric field (object_count or triangle_count), grouped 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",
     "object_count",
     "triangle_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
     },
     "object_count": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "triangle_count": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "asset_group": "group-a",
     "object_count": 10,
     "triangle_count": 1
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "asset_group": "group-b",
     "object_count": 20,
     "triangle_count": 2
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "asset_group": "group-a",
     "object_count": 15,
     "triangle_count": 3
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "asset_group": "group-b",
     "object_count": 30,
     "triangle_count": 4
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "object_count",
    "triangle_count"
   ],
   "type": "string",
   "default": "object_count"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/scene-geometry-string-normalisation-grouped-numeric-summary-0e15ea90/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)