# Point Clouds — Adjacent Row Changes + Secondary-Measure Weighted Mean

> Point Clouds — Adjacent Row Changes + Secondary-Measure Weighted Mean is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-11-02).

Computes adjacent row changes and secondary-measure weighted mean analytics for point cloud datasets (point_count, file_mb) — up to 200 rows, two reports per call.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-creative-22-159?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-11-02
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/point-clouds-adjacent-row-changes-secondary-measure-weighted-mean-3e820545
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_nnRdvDrdY4TtV5POGb1YG

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 point-clouds-adjacent-row-changes-secondary-measure-weighted-mean-3e820545 -d '<json body>'
```

Example prompt: Can you run adjacent row change analysis and secondary-measure weighted mean on my point cloud data? I have 4 records: row-1 on 2026-10-01 with point_count 10 and file_mb 1 in group-a, row-2 on 2026-10-02 with point_count 20 and file_mb 2 in group-b, row-3 on 2026-10-03 with point_count 15 and file_mb 3 in group-a, row-4 on 2026-10-04 with point_count 30 and file_mb 4 in group-b — analyze by point_count.

## When to prefer this

Choose this endpoint when you have tabular point cloud records with point_count and file_mb measurements and need both sequential delta analysis (row-over-row changes) and a weighted mean summary in a single API call. It is ideal for 3D scanning pipelines, LiDAR data audits, or geospatial asset management workflows where you want lightweight local analytics without any external data lookup or prediction services. Best for datasets up to 200 rows where cost efficiency ($0.01 USDC for two reports) matters.

## Known failure modes

- Fewer than 1 row provided — minimum input validation error
- More than 200 rows submitted — maxItems exceeded error
- Invalid date format (not YYYY-MM-DD) — pattern validation failure
- Missing required fields (row_id, asset_group, date, point_count, file_mb) — schema validation error
- Invalid field enum value (not point_count or file_mb) — enum validation error
- Null values for both numeric fields may produce incomplete or undefined weighted mean results

## How this service works

Point clouds — Adjacent row changes + Secondary-measure weighted mean: Adjacent row changes + Secondary-measure weighted mean for supplied point clouds records (point_count, file_mb). 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 analytical reports for the supplied point cloud rows: (1) an adjacent row change report showing delta values between consecutive records for the selected primary field (point_count or file_mb), and (2) a secondary-measure weighted mean report summarizing the weighted average using the complementary measure as weights. Both reports are 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",
     "point_count",
     "file_mb"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "maxLength": 10
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "file_mb": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "asset_group": {
      "type": "string",
      "default": "",
      "maxLength": 80
     },
     "point_count": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "file_mb": 1,
     "asset_group": "group-a",
     "point_count": 10
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "file_mb": 2,
     "asset_group": "group-b",
     "point_count": 20
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "file_mb": 3,
     "asset_group": "group-a",
     "point_count": 15
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "file_mb": 4,
     "asset_group": "group-b",
     "point_count": 30
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "point_count",
    "file_mb"
   ],
   "type": "string",
   "default": "point_count"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/point-clouds-adjacent-row-changes-secondary-measure-weighted-mean-3e820545/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)