# Join Coverage Analytics — Record Quality Audit, Exact Row Deduplication & Category Frequencies

> Join Coverage Analytics — Record Quality Audit, Exact Row Deduplication & Category Frequencies 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 three local analytical reports on join coverage data (matched_rows, source_rows): record quality audit, exact row deduplication, and category frequency analysis — all in a single call for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-09-212?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-analytics-record-quality-audit-exact-row-deduplication-9efa477a
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_qzhjznyQACTshm43uAgaM

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-9efa477a -d '<json body>'
```

Example prompt: Can you audit these join coverage records for quality issues, remove any exact duplicates, and give me a frequency breakdown by dataset_group? I have 4 rows: row-1 on 2026-10-01 with source_rows=1, matched_rows=10, group-a; row-2 on 2026-10-02 with source_rows=2, matched_rows=20, group-b; row-3 on 2026-10-03 with source_rows=3, matched_rows=15, group-a; row-4 on 2026-10-04 with source_rows=4, matched_rows=30, group-b.

## When to prefer this

Choose this endpoint when you need all three of record quality auditing, exact deduplication, and category frequency analysis on join coverage data (matched_rows, source_rows fields) in a single low-cost call. It is ideal for data engineers who want a bundled analytical pass on up to 200 join coverage rows without standing up local tooling. Prefer alternatives if you need only one of the three reports, need more than 200 rows, require fuzzy deduplication, or need live/external data lookups.

## Known failure modes

- Submitting more than 200 rows returns a validation error
- Missing required fields (row_id, dataset_group, date, matched_rows, source_rows) cause row-level rejection
- Malformed date strings not matching YYYY-MM-DD pattern are flagged or rejected
- numeric values outside ±1,000,000,000,000 range are rejected
- Empty rows array returns an error
- Payment failure (insufficient USDC balance) blocks the request

## How this service works

Join coverage — Record quality audit + Exact row deduplication + Category frequencies: Record quality audit + Exact row deduplication + Category frequencies 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 flagging nulls, out-of-range values, and format issues in the supplied rows; (2) an exact row deduplication report identifying and removing identical records; and (3) a category frequency table showing how often each dataset_group value appears. All 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",
     "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-analytics-record-quality-audit-exact-row-deduplication-9efa477a/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)