# Join Coverage Analytics — Record Quality Audit, Exact Row Deduplication & Numeric Distribution

> Join Coverage Analytics — Record Quality Audit, Exact Row Deduplication & 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 2026-10-19).

Runs three analytical reports (record quality audit, exact row deduplication, and numeric distribution) on up to 200 join coverage records containing matched_rows and source_rows fields.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-09-210?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-analytics-record-quality-audit-exact-row-deduplication-41759305
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_hAeLbn7H0OLWtajgUs8W0

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-analytics-record-quality-audit-exact-row-deduplication-41759305 -d '<json body>'
```

Example prompt: Can you run a record quality audit, exact deduplication check, and numeric distribution on these join coverage records — here are up to 50 rows with matched_rows and source_rows values grouped by dataset_group — and analyze the matched_rows field specifically?

## When to prefer this

Choose this endpoint when you need three combined analytical reports — quality audit, deduplication, and numeric distribution — on join coverage data (matched_rows and source_rows) in a single low-cost call. Ideal for data engineers validating ETL join outputs, QA pipelines profiling dataset coverage metrics, or analysts checking for duplicate records before downstream processing. Best when your dataset fits within 200 rows and you want all three reports at once for $0.01 USDC rather than calling separate endpoints.

## Known failure modes

- More than 200 rows submitted — request will be rejected or truncated
- Missing required fields (row_id, dataset_group, date, matched_rows, source_rows) cause validation errors
- Invalid date format (not YYYY-MM-DD) causes schema rejection
- Numeric values outside allowed range (-1T to +1T) may be rejected
- Empty rows array returns error

## How this service works

Join coverage — Record quality audit + Exact row deduplication + Numeric distribution: Record quality audit + Exact row deduplication + Numeric distribution for supplied join coverage records (matched_rows, source_rows). 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: (1) a record quality audit identifying missing, null, or malformed values across the supplied rows; (2) an exact row deduplication report listing duplicate records; and (3) a numeric distribution summary (e.g. min, max, mean, percentiles) for the selected numeric field (matched_rows or source_rows). All analysis is performed locally on 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",
     "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-analytics-record-quality-audit-exact-row-deduplication-41759305/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)