# Geospatial Tile Processing — Record Quality Audit + IQR Outlier Flags

> Geospatial Tile Processing — Record Quality Audit + IQR Outlier Flags 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).

Runs a record quality audit and IQR-based outlier detection on geospatial tile processing records (tile_count, processing_seconds) for up to 200 rows, returning two independent analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-weather-21-014?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/geospatial-tile-processing-record-quality-audit-iqr-outlier-flags-c569f1f4
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_Mmjboo3-1IBmvEewhKvy6

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 geospatial-tile-processing-record-quality-audit-iqr-outlier-flags-c569f1f4 -d '<json body>'
```

Example prompt: Can you audit these geospatial tile processing records for data quality issues and flag any IQR outliers in tile_count? I have up to 50 rows with row_id, station_group, date, tile_count, and processing_seconds fields.

## When to prefer this

Choose this endpoint when you need to programmatically assess data quality and detect statistical outliers in geospatial tile processing metrics (tile_count or processing_seconds) for batches of up to 200 records. It is ideal for automated data pipeline QA, pre-processing validation before downstream geospatial analysis, or routine audits of tile job logs. Prefer this over generic statistical tools when you need both a quality audit and IQR outlier flagging delivered as two structured reports in a single low-cost call.

## Known failure modes

- Fewer than 1 row submitted — minimum row count not met
- More than 200 rows submitted — exceeds maximum batch size
- Missing required fields (row_id, station_group, date, tile_count, processing_seconds) in one or more rows
- Invalid date format (must match YYYY-MM-DD pattern)
- Invalid field enum value (must be 'tile_count' or 'processing_seconds')
- Payment failure or insufficient USDC balance
- All numeric values are null — IQR computation not possible

## How this service works

Geospatial tile processing — Record quality audit + IQR outlier flags: Record quality audit + IQR outlier flags for supplied geospatial tile processing records (tile_count, processing_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 independent analytical reports: (1) a record quality audit identifying missing values, malformed entries, and data completeness issues across the supplied rows; (2) IQR-based outlier flags identifying which rows contain statistically anomalous values for the selected field (tile_count or processing_seconds), including the specific row_ids flagged as outliers.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/geospatial-tile-processing-record-quality-audit-iqr-outlier-flags-c569f1f4/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)