# Sampling Observations — Record Quality Audit + Exact Row Deduplication + Adjacent Row Changes

> Sampling Observations — Record Quality Audit + Exact Row Deduplication + Adjacent Row Changes is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-15).

Runs three local analytical reports on sampling observation rows: record quality audit, exact row deduplication, and adjacent row change detection for sample_value or sample_weight fields.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-15-217?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-15
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/sampling-observations-record-quality-audit-exact-row-deduplication-43cb47a5
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_yQRKuN8Dpg7Cn1DyiO9W9

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-43cb47a5 -d '<json body>'
```

Example prompt: Can you run a full data quality audit, exact row deduplication check, and adjacent row change detection on my sampling observations — I have rows with row_id, dataset_group, date, sample_value, and sample_weight fields, and I want to analyze the sample_value column? Here are up to 200 rows to check.

## When to prefer this

Choose this endpoint when you need three bundled analytical reports — quality audit, deduplication, and adjacent-row change detection — on sampling observation records in a single low-cost call. It is ideal for datasets up to 200 rows where all analysis can be done locally against supplied data with no need for external data enrichment, predictions, or real-time lookups. It is more cost-effective than calling three separate endpoints when all three report types are needed together.

## Known failure modes

- More than 200 rows submitted — request will be rejected or truncated
- Missing required fields (row_id, date, dataset_group) cause row-level validation errors
- Invalid date format (not YYYY-MM-DD) triggers schema validation failure
- Values outside the allowed range (-1e12 to 1e12) may be rejected
- Empty rows array returns an error
- Payment failure via x402 protocol prevents execution

## How this service works

Sampling observations — Record quality audit + Exact row deduplication + Adjacent row changes: Record quality audit + Exact row deduplication + Adjacent row changes 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 reports for up to 200 supplied rows: (1) a record quality audit flagging nulls, format violations, and anomalies in sample_value/sample_weight; (2) an exact row deduplication report identifying fully identical rows; and (3) an adjacent row changes report showing where consecutive rows differ in the selected field. 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",
     "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-43cb47a5/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)