# Sampling Observations Analytics: Record Quality Audit + String Normalisation + Two-Measure Correlation

> Sampling Observations Analytics: Record Quality Audit + String Normalisation + Two-Measure Correlation 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 local analytical reports on sampling observation records — a data quality audit, string normalisation, and correlation between sample_value and sample_weight — for up to 200 rows in a single call.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-15-204?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/sampling-observations-analytics-record-quality-audit-string-d6f0282a
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_-x9p7h1tQCGB2JihlWOy1

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-analytics-record-quality-audit-string-d6f0282a -d '<json body>'
```

Example prompt: Can you audit the quality of my sampling observation records, normalise the string fields, and compute the correlation between sample_value and sample_weight? I have 4 rows: row-1 on 2026-10-01 in group-a with sample_value=10 and sample_weight=1; row-2 on 2026-10-02 in group-b with sample_value=20 and sample_weight=2; row-3 on 2026-10-03 in group-a with sample_value=15 and sample_weight=3; row-4 on 2026-10-04 in group-b with sample_value=30 and sample_weight=4.

## When to prefer this

Choose this endpoint when you need to simultaneously audit data quality, normalise string fields, and compute correlation for sampling observation data with up to 200 rows in a single low-cost call. It is ideal when you want three bundled analytical reports without setting up separate pipelines, and when all computation should happen locally with no external data access or predictions required.

## Known failure modes

- Empty rows array or rows exceeding 200 items returns a validation error
- Malformed date strings (not matching YYYY-MM-DD) cause row-level rejection
- sample_value or sample_weight outside ±1,000,000,000,000 triggers range error
- Missing required fields (row_id, dataset_group, date) cause schema validation failure
- All-null sample_value or sample_weight columns may produce undefined correlation result

## How this service works

Sampling observations — Record quality audit + String normalisation + Two-measure correlation: Record quality audit + String normalisation + Two-measure correlation 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 for the supplied rows: (1) a record quality audit flagging issues such as nulls, out-of-range values, and malformed fields; (2) a string normalisation report showing standardised versions of text fields like dataset_group; and (3) a two-measure correlation report quantifying the statistical relationship between sample_value and sample_weight. All computation is local 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-analytics-record-quality-audit-string-d6f0282a/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)