# Sampling Observations — Record Quality Audit + Category Frequencies

> Sampling Observations — Record Quality Audit + 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 2026-10-19).

Runs two local analytical reports on supplied sampling observation rows: a record quality audit and a category frequency breakdown, for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-15-006?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-19
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/sampling-observations-record-quality-audit-category-frequencies-b53b666f
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_x6pPL0_9dq0clC04hhKkb

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 sampling-observations-record-quality-audit-category-frequencies-b53b666f -d '<json body>'
```

Example prompt: Can you run a record quality audit and category frequency report on my sampling observations? Here are up to 200 rows with row_id, dataset_group, date, sample_value, and sample_weight — I want to know which records have quality issues and how frequently each group appears.

## When to prefer this

Choose this endpoint when you need both a data quality audit and a category frequency summary on a batch of sampling observation records in a single low-cost call. It is ideal for pre-analysis validation of survey, clinical, or market research samples where sample_value and sample_weight are key fields and dataset groups need frequency profiling. It does not perform predictions, external lookups, or professional assessments.

## Known failure modes

- Exceeding 200 rows returns a validation error
- Rows missing required fields (row_id, dataset_group, date, sample_value, sample_weight) will fail schema validation
- Dates not matching YYYY-MM-DD pattern will be rejected
- Numeric values outside ±1,000,000,000,000 will fail validation
- Empty rows array (minItems: 1 not met) returns an error
- Payment failure results in no report being generated

## How this service works

Sampling observations — Record quality audit + Category frequencies: Record quality audit + Category frequencies for supplied sampling observations records (sample_value, sample_weight). 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 issues such as nulls, out-of-range values, or malformed fields across the supplied rows, and (2) a category frequency table showing how often each dataset_group value appears in the dataset. Both reports are computed locally from the supplied data with no external lookups.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/sampling-observations-record-quality-audit-category-frequencies-b53b666f/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)