# Join Coverage Record Quality Audit & Numeric Distribution

> Join Coverage Record Quality Audit & 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 2026-10-23).

Runs two local analytical reports—record quality audit and numeric distribution—on up to 200 join coverage rows containing matched_rows and source_rows fields.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-09-004?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-23
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/join-coverage-record-quality-audit-numeric-distribution-8d041270
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_K1Ufg1Ri9f052WY352GYJ

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 join-coverage-record-quality-audit-numeric-distribution-8d041270 -d '<json body>'
```

Example prompt: Run a record quality audit and numeric distribution report on my join coverage data — I have 4 rows with matched_rows values of 10, 20, 15, 30 and source_rows of 1, 2, 3, 4, grouped as group-a and group-b, and I want the distribution report focused on matched_rows.

## When to prefer this

Choose this endpoint when you need lightweight, offline data profiling for join coverage datasets without any external lookups or ML predictions — ideal for ETL validation workflows, data quality gates, and auditing matched vs. source row counts across dataset groups. Prefer it over heavier analytics platforms when you have up to 200 rows and need two quick reports (quality audit + numeric distribution) at minimal cost.

## Known failure modes

- Submitting more than 200 rows returns a validation error
- Missing required row fields (row_id, dataset_group, date, matched_rows, source_rows) causes a schema validation failure
- Invalid date format (not YYYY-MM-DD) triggers a pattern validation error
- Numeric values outside the allowed range (-1,000,000,000,000 to 1,000,000,000,000) are rejected
- An empty rows array (minItems:1 violated) returns an error
- Invalid field enum value (not 'matched_rows' or 'source_rows') causes rejection

## How this service works

Join coverage — Record quality audit + Numeric distribution: Record quality audit + Numeric distribution for supplied join coverage records (matched_rows, source_rows). 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 computed locally: (1) a record quality audit assessing completeness, nulls, and validity of the submitted join coverage rows; and (2) a numeric distribution report for the selected field (matched_rows or source_rows), including statistical summaries such as min, max, mean, percentiles, and frequency distribution across up to 200 rows.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/join-coverage-record-quality-audit-numeric-distribution-8d041270/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)