# Reservoir Observations Data Quality Audit — Record Quality, String Normalisation & IQR Outlier Flags

> Reservoir Observations Data Quality Audit — Record Quality, String Normalisation & 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 2026-10-24).

Runs three analytical reports on reservoir observation records (stored_m3, capacity_m3): record quality audit, string normalisation, and IQR-based outlier detection — no external lookups or predictions.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-weather-19-203?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-24
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/reservoir-observations-data-quality-audit-record-quality-string-a7f3ef2e
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_3-UEW_-VQhsIu8_MvNoP3

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 reservoir-observations-data-quality-audit-record-quality-string-a7f3ef2e -d '<json body>'
```

Example prompt: Can you run a full data quality audit, string normalisation, and IQR outlier check on this batch of reservoir observation records — I have up to 150 rows with stored_m3 and capacity_m3 fields, grouped by station, and I want to flag the stored_m3 values for outliers?

## When to prefer this

Choose this endpoint when you have reservoir-specific observation data (stored_m3, capacity_m3) and need all three quality checks — record audit, string normalisation, and IQR outlier detection — in a single call for up to 200 rows. Prefer it over generic data quality tools when your data specifically models reservoir storage and capacity by station group and date, and you want a combined multi-report output without external lookups or predictions.

## Known failure modes

- Exceeding 200 rows returns a validation error
- Missing required fields (row_id, date, station_group, stored_m3, capacity_m3) cause row-level rejection
- Invalid date format (non-YYYY-MM-DD) triggers pattern validation failure
- Numeric values outside ±1,000,000,000,000 are rejected by schema
- Empty rows array returns a schema validation error
- Selecting an invalid field enum value causes a request error

## How this service works

Reservoir observations — Record quality audit + String normalisation + IQR outlier flags: Record quality audit + String normalisation + IQR outlier flags for supplied reservoir observations records (stored_m3, capacity_m3). Up to 200 rows; 3 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 3 supplied-data reports for up to 200 rows.

## Output

Three structured analytical reports: (1) a record quality audit identifying missing values, malformed dates, and field-level issues; (2) a string normalisation report for station_group and other text fields; (3) an IQR outlier flag report identifying statistically anomalous stored_m3 or capacity_m3 values across the submitted rows.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "rows": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "row_id",
     "station_group",
     "date",
     "stored_m3",
     "capacity_m3"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "maxLength": 10
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "stored_m3": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "capacity_m3": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "station_group": {
      "type": "string",
      "default": "",
      "maxLength": 80
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "stored_m3": 10,
     "capacity_m3": 1,
     "station_group": "group-a"
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "stored_m3": 20,
     "capacity_m3": 2,
     "station_group": "group-b"
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "stored_m3": 15,
     "capacity_m3": 3,
     "station_group": "group-a"
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "stored_m3": 30,
     "capacity_m3": 4,
     "station_group": "group-b"
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "stored_m3",
    "capacity_m3"
   ],
   "type": "string",
   "default": "stored_m3"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/reservoir-observations-data-quality-audit-record-quality-string-a7f3ef2e/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)