# Coordinate Quality Checks — Numeric Distribution + Date by Category Pivot

> Coordinate Quality Checks — Numeric Distribution + 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 2026-10-26).

Analyzes coordinate quality check records by producing two local statistical reports: a numeric distribution for checked_points or flagged_points, and a date-by-station-group pivot table.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-weather-23-083?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-26
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/coordinate-quality-checks-numeric-distribution-date-by-category-pivot-66f21b45
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_QBj5DFJwQv19DHdDUizUb

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 coordinate-quality-checks-numeric-distribution-date-by-category-pivot-66f21b45 -d '<json body>'
```

Example prompt: I have coordinate quality check records for two station groups over several days — can you run a numeric distribution on checked_points and pivot flagged_points by station group and date? Here's my data: row-1, group-a, 2026-10-01, checked=10, flagged=1; row-2, group-b, 2026-10-02, checked=20, flagged=2; row-3, group-a, 2026-10-03, checked=15, flagged=3.

## When to prefer this

Choose this endpoint when you have up to 200 rows of coordinate quality check records (with checked_points and flagged_points fields) and need both a numeric distribution and a date-by-category pivot in a single low-cost call ($0.01 USDC). It operates entirely on supplied data with no external lookups, making it fast and deterministic. Prefer it over general-purpose analytics when your data fits the coordinate quality check schema with station_group and date dimensions.

## Known failure modes

- More than 200 rows submitted — request rejected or truncated
- Missing required fields (row_id, station_group, date, checked_points, or flagged_points) — validation error
- Invalid date format (must match YYYY-MM-DD) — schema validation failure
- Numeric values outside allowed range — rejection
- Empty rows array — error returned

## How this service works

Coordinate quality checks — Numeric distribution + Date by category pivot: Numeric distribution + Date by category pivot for supplied coordinate quality checks records (checked_points, flagged_points). 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 computed locally from the supplied rows: (1) a numeric distribution summary (e.g. min, max, mean, percentiles, histogram bins) for the selected field (checked_points or flagged_points), and (2) a pivot table of date by station_group category showing aggregated values. Up to 200 rows supported per call.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/coordinate-quality-checks-numeric-distribution-date-by-category-pivot-66f21b45/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)