# Humidity Observations Data Quality Audit, String Normalisation & Category Frequencies

> Humidity Observations Data Quality Audit, String Normalisation & Category Frequencies is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-29).

Runs three analytical reports on supplied humidity observation records: a record quality audit, string normalisation, and category frequency analysis — all offline, up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-weather-04-195?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-29
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/humidity-observations-data-quality-audit-string-normalisation-01bcba4c
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_CP8OvUVVyZrXAt8PN_RCs

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 humidity-observations-data-quality-audit-string-normalisation-01bcba4c -d '<json body>'
```

Example prompt: Can you audit the quality of these humidity observation records, normalise the station group strings, and give me category frequencies? I have about 150 rows with fields like row_id, station_group, date, humidity_percent, and observation_count.

## When to prefer this

Choose this endpoint when you need to quickly audit, clean, and summarise humidity observation records without any external data dependencies. It is ideal for pre-processing pipelines where you need all three reports (quality audit, string normalisation, category frequencies) in a single cheap call ($0.01 USDC) on batches up to 200 rows. Prefer alternatives if you need live weather lookups, predictive modelling, or processing more than 200 rows at once.

## Known failure modes

- Exceeding 200 rows returns a validation error
- Missing required fields (row_id, station_group, date, humidity_percent, observation_count) cause row-level rejection
- Invalid date format (non-YYYY-MM-DD) triggers pattern validation failure
- Empty rows array returns an error
- Null numeric values may be flagged in the quality audit rather than causing failure

## How this service works

Humidity observations — Record quality audit + String normalisation + Category frequencies: Record quality audit + String normalisation + Category frequencies for supplied humidity observations records (humidity_percent, observation_count). 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

Returns three independent reports for the supplied rows: (1) a record quality audit flagging data issues, (2) normalised string values for text fields such as station_group, and (3) category frequency counts showing how often each distinct category value appears. All analysis is performed locally on the supplied data with no external lookups.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "rows": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "row_id",
     "station_group",
     "date",
     "humidity_percent",
     "observation_count"
    ],
    "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
     },
     "humidity_percent": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "observation_count": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "station_group": "group-a",
     "humidity_percent": 10,
     "observation_count": 1
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "station_group": "group-b",
     "humidity_percent": 20,
     "observation_count": 2
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "station_group": "group-a",
     "humidity_percent": 15,
     "observation_count": 3
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "station_group": "group-b",
     "humidity_percent": 30,
     "observation_count": 4
    }
   ],
   "maxItems": 200,
   "minItems": 1
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/humidity-observations-data-quality-audit-string-normalisation-01bcba4c/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)