# Camera Coverage Analytics: Adjacent Row Changes + Date-by-Category Pivot

> Camera Coverage Analytics: Adjacent Row Changes + 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).

Runs two analytical reports on camera coverage data — adjacent row change detection and a date-by-category pivot — for up to 200 rows of shot_count or coverage_seconds data.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-creative-12-160?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/camera-coverage-analytics-adjacent-row-changes-date-by-category-pivot-ef5bb6a6
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_WDxGW4PVHSWjuNof1dNGv

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 camera-coverage-analytics-adjacent-row-changes-date-by-category-pivot-ef5bb6a6 -d '<json body>'
```

Example prompt: I have 4 camera coverage records with shot_count values — can you run adjacent row change detection and a date-by-category pivot on them? The rows are: row-1 on 2026-10-01 with shot_count 10 for group-a, row-2 on 2026-10-02 with shot_count 20 for group-b, row-3 on 2026-10-03 with shot_count 15 for group-a, and row-4 on 2026-10-04 with shot_count 30 for group-b.

## When to prefer this

Choose this endpoint when you have camera coverage tabular data (shot_count or coverage_seconds) with row IDs, dates, and asset groups, and you need both a sequential row-difference analysis and a date-by-category pivot in a single low-cost call. It is ideal for small-to-medium datasets (up to 200 rows) where no live data lookup, external enrichment, or prediction is needed — just fast local analytical computation on supplied records.

## Known failure modes

- Fewer than 1 row supplied — returns a validation error
- More than 200 rows supplied — rejected with a row limit error
- Invalid date format (not YYYY-MM-DD) in any row — schema validation failure
- Invalid field value (not 'shot_count' or 'coverage_seconds') — enum validation error
- Missing required fields (row_id, asset_group, date) in any row — schema error
- Null numeric values handled gracefully but may produce null deltas in adjacent row report

## How this service works

Camera coverage — Adjacent row changes + Date by category pivot: Adjacent row changes + Date by category pivot for supplied camera coverage records (shot_count, coverage_seconds). 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 derived entirely from the supplied data: (1) an adjacent row changes report showing how shot_count or coverage_seconds values differ between consecutive rows, and (2) a date-by-category pivot table aggregating the selected metric by date and asset_group. No external lookups or predictions are made; all computation is local to the engine.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "rows": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "row_id",
     "asset_group",
     "date",
     "shot_count",
     "coverage_seconds"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "maxLength": 10
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "shot_count": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "asset_group": {
      "type": "string",
      "default": "",
      "maxLength": 80
     },
     "coverage_seconds": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "shot_count": 10,
     "asset_group": "group-a",
     "coverage_seconds": 1
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "shot_count": 20,
     "asset_group": "group-b",
     "coverage_seconds": 2
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "shot_count": 15,
     "asset_group": "group-a",
     "coverage_seconds": 3
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "shot_count": 30,
     "asset_group": "group-b",
     "coverage_seconds": 4
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "shot_count",
    "coverage_seconds"
   ],
   "type": "string",
   "default": "shot_count"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/camera-coverage-analytics-adjacent-row-changes-date-by-category-pivot-ef5bb6a6/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)