# Schema Conformity — Record Quality Audit + Missing-Value Fill

> Schema Conformity — Record Quality Audit + Missing-Value Fill 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).

Audits data quality of schema conformity records (valid_records, checked_records) and fills missing values using zero, mean, or median imputation — two independent reports for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-02-019?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-missing-value-fill-1168fa80
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_msL_2dZ_IQjXuN4RmcBTU

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-missing-value-fill-1168fa80 -d '<json body>'
```

Example prompt: Audit the quality of my schema conformity records and fill any missing values in the valid_records column using median imputation — I have 4 rows: row-1 for group-a on 2026-10-01 with valid_records=10, checked_records=1; row-2 for group-b on 2026-10-02 with valid_records=20, checked_records=null; row-3 for group-a on 2026-10-03 with valid_records=null, checked_records=3; row-4 for group-b on 2026-10-04 with valid_records=30, checked_records=4.

## When to prefer this

Choose this endpoint when you need both a data quality audit and missing-value imputation for schema conformity metrics (valid_records, checked_records) in a single low-cost call. It is ideal for batch offline analysis of up to 200 rows where no live data fetching, machine learning prediction, or external enrichment is needed. Prefer it over general-purpose data tools when you specifically track schema validation pass rates and need reproducible, locally computed imputation.

## Known failure modes

- Exceeding 200 rows returns a validation error
- Missing required fields (row_id, date, dataset_group) causes row rejection
- Invalid date format (not YYYY-MM-DD) triggers a pattern validation error
- Values outside ±1,000,000,000,000 are rejected by schema
- Invalid method enum value (not zero/mean/median) causes a bad request error
- Empty rows array (minItems:1 violated) returns an error

## How this service works

Schema conformity — Record quality audit + Explicit missing-value fill: Record quality audit + Explicit missing-value fill 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 identifying problematic, missing, or out-of-range values across the submitted rows, and (2) a missing-value fill report showing the original and imputed values for the chosen field (valid_records or checked_records) using the selected method (zero, mean, or median). Results are 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
  },
  "field": {
   "enum": [
    "valid_records",
    "checked_records"
   ],
   "type": "string",
   "default": "valid_records"
  },
  "method": {
   "enum": [
    "zero",
    "mean",
    "median"
   ],
   "type": "string",
   "default": "median"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/schema-conformity-record-quality-audit-missing-value-fill-1168fa80/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)