# Schema Conformity Analytics — Record Quality Audit, String Normalisation & Base-100 Series

> Schema Conformity Analytics — Record Quality Audit, String Normalisation & Base-100 Series is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-14).

Runs three analytical reports (record quality audit, string normalisation, and base-100 rebase series) 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-02-201?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-14
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/schema-conformity-analytics-record-quality-audit-string-normalisation-6454ca1e
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_C-EtpW5QheXVGQNP1fAlP

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-6454ca1e -d '<json body>'
```

Example prompt: Can you run the three conformity analytics reports — record quality audit, string normalisation, and base-100 series — on my schema conformity dataset? I have 4 rows: row-1 for group-a on 2026-10-01 with 10 valid and 1 checked, row-2 for group-b on 2026-10-02 with 20 valid and 2 checked, row-3 for group-a on 2026-10-03 with 15 valid and 3 checked, row-4 for group-b on 2026-10-04 with 30 valid and 4 checked — use valid_records as the field and row index 0 as the base.

## When to prefer this

Choose this endpoint when you need three combined conformity analytics reports in a single $0.01 call on up to 200 rows of schema validation data. It is ideal for batch auditing of dataset quality logs where valid_records and checked_records are the key metrics, and you want quality audit, string normalisation, and a base-100 trend series without any external data lookups or live predictions.

## Known failure modes

- More than 200 rows submitted — endpoint rejects input exceeding maxItems limit
- Missing required fields (row_id, date, valid_records, checked_records) causes validation error
- Date not matching YYYY-MM-DD pattern results in schema rejection
- base_index out of range (0–199) causes parameter error
- Null values in numeric fields may affect base-100 calculation accuracy
- Invalid field enum value (not valid_records or checked_records) returns error

## How this service works

Schema conformity — Record quality audit + String normalisation + Base-100 series: Record quality audit + String normalisation + Base-100 series 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 delivered together: (1) a record quality audit summarising completeness and anomalies in valid_records and checked_records, (2) a string normalisation report cleaning and standardising text fields like dataset_group, and (3) a base-100 index series rebasing the chosen numeric field relative to the specified base row — all computed locally without external lookups.

## 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"
  },
  "base_index": {
   "type": "integer",
   "default": 0,
   "maximum": 199,
   "minimum": 0
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/schema-conformity-analytics-record-quality-audit-string-normalisation-6454ca1e/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)