# Join Coverage Record Quality Audit and Two-Measure Correlation

> Join Coverage Record Quality Audit and Two-Measure Correlation is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-19).

Audits record quality and computes two-measure correlation for join coverage data (matched_rows, source_rows) across up to 200 supplied rows, producing two independent analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-09-015?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-19
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/join-coverage-record-quality-audit-and-two-measure-correlation-5f429b37
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_JBt-r02m719Skd6MZKIvS

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-and-two-measure-correlation-5f429b37 -d '<json body>'
```

Example prompt: Can you audit the quality of these join coverage records and check the correlation between matched_rows and source_rows? I have 4 rows across groups 'group-a' and 'group-b' from October 2026 — row-1 has source_rows=1 and matched_rows=10, row-2 has source_rows=2 and matched_rows=20, row-3 has source_rows=3 and matched_rows=15, row-4 has source_rows=4 and matched_rows=30.

## When to prefer this

Choose this endpoint when you have join coverage data with matched_rows and source_rows metrics and need both a record quality audit and a correlation analysis in a single call at low cost ($0.01 USDC). Ideal for data engineers and analysts who want offline, local analytical processing of up to 200 rows without any external lookups or live data access. Best when you already have the join coverage records in hand and need structured quality and correlation reports quickly.

## Known failure modes

- More than 200 rows submitted — request rejected due to maxItems limit
- Missing required fields (row_id, dataset_group, date, matched_rows, source_rows) — validation error
- Invalid date format (must match YYYY-MM-DD pattern) — schema validation failure
- Numeric values outside allowed range (±1,000,000,000,000) — schema rejection
- Empty rows array — minItems:1 violation
- Payment not included or insufficient — x402 payment required error

## How this service works

Join coverage — Record quality audit + Two-measure correlation: Record quality audit + Two-measure correlation 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: (1) a record quality audit highlighting missing values, anomalies, and completeness issues across the supplied join coverage rows, and (2) a two-measure correlation analysis between matched_rows and source_rows across the dataset. No external lookups or predictions are made; analysis is performed locally on the supplied data only.

## 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
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/join-coverage-record-quality-audit-and-two-measure-correlation-5f429b37/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)