# Sampling Observations — Record Quality Audit + Exact Row Deduplication + IQR Outlier Flags

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

Runs three local analytical reports on up to 200 sampling observation rows: a record quality audit, exact row deduplication, and IQR-based outlier detection for sample_value or sample_weight.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-15-220?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-exact-row-deduplication-f5db3d2b
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_yShuM_qhSMkoMnOiedaxh

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-exact-row-deduplication-f5db3d2b -d '<json body>'
```

Example prompt: Can you audit my sampling observations for quality issues, exact duplicates, and IQR outlier flags? I have up to 50 rows with fields like row_id, dataset_group, date, sample_value, and sample_weight — run all three reports on the sample_value field.

## When to prefer this

Choose this endpoint when you need three simultaneous data quality reports (quality audit, deduplication, and IQR outlier detection) on sampling observation records in a single low-cost call. Ideal for pre-analysis data cleaning pipelines where sample_value and sample_weight are the key numeric fields. Best suited for datasets under 200 rows that require offline, deterministic analysis with no external data lookups or predictions.

## Known failure modes

- Exceeding 200 rows returns a validation error
- Missing required fields (row_id, dataset_group, date, sample_value, sample_weight) causes schema rejection
- Invalid date format (non-YYYY-MM-DD) fails pattern validation
- Numeric values outside [-1e12, 1e12] range are rejected
- Empty rows array is rejected (minItems: 1)
- Invalid field enum value (anything other than sample_value or sample_weight) causes error

## How this service works

Sampling observations — Record quality audit + Exact row deduplication + IQR outlier flags: Record quality audit + Exact row deduplication + IQR outlier flags for supplied sampling observations records (sample_value, sample_weight). 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 analytical reports: (1) a record quality audit identifying missing, malformed, or invalid field values; (2) an exact row deduplication report listing duplicate records; and (3) IQR-based outlier flags for the selected numeric field (sample_value or sample_weight). All reports are computed locally 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
  },
  "field": {
   "enum": [
    "sample_value",
    "sample_weight"
   ],
   "type": "string",
   "default": "sample_value"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/sampling-observations-record-quality-audit-exact-row-deduplication-f5db3d2b/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)