# Schema Conformity Analytics — Record Quality Audit, String Normalisation & Numeric Distribution

> Schema Conformity Analytics — Record Quality Audit, String Normalisation & Numeric Distribution is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-18).

Runs three local analytical reports (record quality audit, string normalisation, and numeric distribution) on up to 200 rows of schema conformity data containing valid_records and checked_records fields.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-02-193?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-18
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/schema-conformity-analytics-record-quality-audit-string-normalisation-e9995568
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_76qfVQh4C6z8w41JQeU8C

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 schema-conformity-analytics-record-quality-audit-string-normalisation-e9995568 -d '<json body>'
```

Example prompt: Can you run a full quality audit, string normalisation, and numeric distribution analysis on my schema conformity data? Here are 4 rows: row-1 on 2026-10-01 for group-a with valid_records=10 and checked_records=1, row-2 on 2026-10-02 for group-b with valid_records=20 and checked_records=2, row-3 on 2026-10-03 for group-a with valid_records=15 and checked_records=3, and row-4 on 2026-10-04 for group-b with valid_records=30 and checked_records=4 — analyse the valid_records field.

## When to prefer this

Choose this endpoint when you need three simultaneous local analytical reports (quality audit + string normalisation + numeric distribution) on schema conformity row data without any external lookups, predictions, or side effects. It is ideal for lightweight, offline data profiling of up to 200 validation records at a low fixed cost of $0.01 USDC for all three reports together. Prefer alternatives if you need live data fetching, ML-based predictions, or analysis of more than 200 rows.

## Known failure modes

- Fewer than 1 row supplied — request rejected
- More than 200 rows supplied — exceeds maximum batch size
- Row missing required fields (row_id, date, valid_records, checked_records) — validation error
- Date field does not match YYYY-MM-DD pattern — schema rejection
- field enum value not one of valid_records or checked_records — invalid input
- Numeric values outside allowed range (±1 trillion) — schema rejection
- Payment of 0.01 USDC not included or fails — 402 Payment Required

## How this service works

Schema conformity — Record quality audit + String normalisation + Numeric distribution: Record quality audit + String normalisation + Numeric distribution for supplied schema conformity records (valid_records, checked_records). 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

Three independent analytical reports generated from the supplied rows: (1) a record quality audit flagging missing values, format issues, and validity ratio anomalies; (2) a string normalisation report on text fields like dataset_group; and (3) a numeric distribution summary (min, max, mean, spread, etc.) for the selected field (valid_records or checked_records). All processing is local — no external lookups or predictions are made.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/schema-conformity-analytics-record-quality-audit-string-normalisation-e9995568/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)