# Schema Conformity Analytics — Record Quality Audit, String Normalisation & Category Frequencies

> Schema Conformity Analytics — Record Quality Audit, String Normalisation & Category Frequencies 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 bundled analytical reports (record quality audit, string normalisation, and category frequency breakdown) on up to 200 schema conformity rows containing valid_records and checked_records fields.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-02-195?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-7124e305
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_MOt2Fq5DrqGlcIbNfjEs4

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-7124e305 -d '<json body>'
```

Example prompt: Can you run a quality audit, string normalisation, and category frequency analysis on my schema conformity records? I have 4 rows: row-1 for group-a on 2026-10-01 with 10 valid out of 1 checked, row-2 for group-b on 2026-10-02 with 20 valid out of 2 checked, row-3 for group-a on 2026-10-03 with 15 valid out of 3 checked, and row-4 for group-b on 2026-10-04 with 30 valid out of 4 checked.

## When to prefer this

Choose this endpoint when you need three bundled local analytical reports — quality audit, string normalisation, and category frequency — on schema conformity data in a single low-cost call ($0.01 USDC). It is best suited for datasets up to 200 rows where you want offline, deterministic analysis with no external API calls or predictions. Prefer alternatives if you need live data lookups, ML-based predictions, or processing more than 200 rows at once.

## Known failure modes

- Submitting more than 200 rows returns a validation error
- Missing required fields (row_id, date, valid_records, checked_records) causes row-level rejection
- Dates not matching YYYY-MM-DD pattern fail schema validation
- Numeric values outside ±1,000,000,000,000 are rejected
- Empty rows array returns an error
- Payment failure (insufficient USDC balance) blocks the request

## How this service works

Schema conformity — Record quality audit + String normalisation + Category frequencies: Record quality audit + String normalisation + Category frequencies 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

Returns three independent analytical reports for the supplied schema conformity rows: (1) a record quality audit summarizing valid vs checked record ratios and flagging anomalies, (2) a string normalisation report cleaning and standardising text fields like dataset_group and row_id, and (3) a category frequency table showing how often each dataset_group appears across the supplied rows. All computed locally with no 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
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/schema-conformity-analytics-record-quality-audit-string-normalisation-7124e305/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)