# Camera Coverage String Normalisation + Adjacent Row Changes

> Camera Coverage String Normalisation + Adjacent Row Changes 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).

Normalises string fields and computes adjacent row changes for camera coverage records (shot_count, coverage_seconds) across up to 200 rows, returning 2 analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-creative-12-029?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/camera-coverage-string-normalisation-adjacent-row-changes-cc9c0edc
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_FLz9Hg6WikdeHDBkxamy-

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-string-normalisation-adjacent-row-changes-cc9c0edc -d '<json body>'
```

Example prompt: I have 4 rows of camera coverage data — row-1 on 2026-10-01 for group-a with shot_count 10 and coverage_seconds 1, row-2 on 2026-10-02 for group-b with shot_count 20 and coverage_seconds 2, row-3 on 2026-10-03 for group-a with shot_count 15 and coverage_seconds 3, row-4 on 2026-10-04 for group-b with shot_count 30 and coverage_seconds 4 — can you run string normalisation and adjacent row change analysis on the shot_count field and give me both reports?

## When to prefer this

Choose this endpoint when you have camera coverage tabular data (shot counts and coverage seconds by date and asset group) and need both string normalisation of categorical fields and adjacent row change detection in a single low-cost call. It is purpose-built for creative/film production data pipelines and costs only $0.01 USDC for two reports on up to 200 rows, making it ideal for lightweight batch QA without requiring any external data sources or live APIs.

## Known failure modes

- More than 200 rows submitted — request rejected due to maxItems constraint
- Missing required fields (row_id, asset_group, date, shot_count, coverage_seconds) — validation error
- Invalid date format (must match YYYY-MM-DD pattern) — schema validation failure
- Numeric values outside allowed range (±1,000,000,000,000) — validation error
- Invalid field enum value (must be 'shot_count' or 'coverage_seconds') — rejected
- Payment not received or insufficient USDC — x402 payment required error

## How this service works

Camera coverage — String normalisation + Adjacent row changes: String normalisation + Adjacent row changes 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

Returns two analytical reports: (1) a string normalisation report cleaning the asset_group field across all submitted rows, and (2) an adjacent row changes report showing consecutive differences in the selected numeric field (shot_count or coverage_seconds) across up to 200 rows. No external lookups or predictions are performed.

## 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-string-normalisation-adjacent-row-changes-cc9c0edc/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)