# Schema Conformity — Record Quality Audit + Date by Category Pivot

> Schema Conformity — Record Quality Audit + Date by Category Pivot is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-17).

Runs two analytical reports on schema conformity records: a record quality audit and a date-by-category pivot, for up to 200 rows of valid_records and checked_records data.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-02-017?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-17
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/schema-conformity-record-quality-audit-date-by-category-pivot-3df1384e
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_wHeQ2ng4tcCClDTrgSBE9

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-record-quality-audit-date-by-category-pivot-3df1384e -d '<json body>'
```

Example prompt: Can you run a record quality audit and a date-by-category pivot on our schema conformity data? I have up to 50 rows with fields row_id, dataset_group, date, valid_records, and checked_records — analyze the valid_records field.

## When to prefer this

Choose this endpoint when you need two combined analytical reports — a record quality audit and a date-by-category pivot — on schema conformity data in a single low-cost API call. Ideal for data engineers or QA pipelines that track valid vs. checked record counts across dataset groups over time and need quick, local analytics without external dependencies. Best for datasets up to 200 rows where cost efficiency ($0.01 for two reports) and no-side-effect computation are priorities.

## Known failure modes

- Input array exceeds 200 rows — request rejected
- Missing required fields (row_id, date, valid_records, checked_records) — validation error
- Invalid date format (must be YYYY-MM-DD) — schema rejection
- Numeric values out of bounds (±1 trillion limit) — validation failure
- Empty rows array — minimum 1 item required
- Invalid field enum value — must be 'valid_records' or 'checked_records'

## How this service works

Schema conformity — Record quality audit + Date by category pivot: Record quality audit + Date by category pivot for supplied schema conformity records (valid_records, checked_records). Up to 200 rows; 2 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 2 supplied-data reports for up to 200 rows.

## Output

Returns two independent analytical reports: (1) a record quality audit summarizing conformity metrics such as validity rates, anomalies, and completeness across rows, and (2) a date-by-category pivot table breaking down the selected field (valid_records or checked_records) by date and dataset_group. Both reports are computed locally from the supplied data 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
  },
  "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-record-quality-audit-date-by-category-pivot-3df1384e/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)