# Sampling Observations Analytics: Record Quality Audit + String Normalisation + Trailing Mean Series

> Sampling Observations Analytics: Record Quality Audit + String Normalisation + Trailing Mean Series 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 records: a record quality audit, string normalisation, and a trailing mean series computation.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-15-199?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-analytics-record-quality-audit-string-3388811b
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_96k-rMpz1BgUO571-xz3D

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-3388811b -d '<json body>'
```

Example prompt: Can you run a quality audit, string normalisation, and trailing mean series (window of 3) on my sampling observations dataset — it has about 50 rows with sample_value and sample_weight fields, grouped by dataset_group, dated from 2026-09-01 to 2026-10-20?

## When to prefer this

Choose this endpoint when you have up to 200 sampling observation records (with sample_value and sample_weight) and need all three of: a data quality audit, string normalisation, and a trailing mean time series — bundled for $0.01 USDC. Ideal for pre-processing pipelines before statistical analysis, where catching data issues and computing rolling averages in a single call saves cost and round-trips. Not suitable for live data lookups, predictions, or datasets exceeding 200 rows.

## Known failure modes

- Fewer than 1 or more than 200 rows submitted — rejected with validation error
- Invalid date format (not YYYY-MM-DD) causes row rejection
- sample_value or sample_weight outside ±1,000,000,000,000 range causes validation failure
- Invalid field enum value (not 'sample_value' or 'sample_weight') returns error
- Window size less than 2 or greater than 200 causes parameter rejection
- Malformed JSON body returns 400-level error
- Payment not provided or insufficient USDC causes 402 Payment Required response

## How this service works

Sampling observations — Record quality audit + String normalisation + Trailing mean series: Record quality audit + String normalisation + Trailing mean series 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 flagging missing, invalid, or anomalous entries across up to 200 rows; (2) a string normalisation report cleaning and standardising text fields like row_id and dataset_group; and (3) a trailing mean series computed over the specified numeric field (sample_value or sample_weight) using the specified rolling window size.

## 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"
  },
  "window": {
   "type": "integer",
   "default": 2,
   "maximum": 200,
   "minimum": 2
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/sampling-observations-analytics-record-quality-audit-string-3388811b/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)