# Join Coverage Analytics: Numeric Distribution + Adjacent Row Changes

> Join Coverage Analytics: Numeric Distribution + Adjacent Row Changes is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-20).

Analyzes join coverage data (matched_rows, source_rows) by producing two local analytical reports: a numeric distribution summary and an adjacent row change analysis, for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-09-077?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-20
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/join-coverage-analytics-numeric-distribution-adjacent-row-changes-25b84361
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_w3DOkEQWMBwiG643WcNEM

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-numeric-distribution-adjacent-row-changes-25b84361 -d '<json body>'
```

Example prompt: Can you analyze these 4 join coverage rows for me — I want both a numeric distribution and adjacent row change report on the matched_rows field: row-1 on 2026-10-01 (source=1, matched=10, group=group-a), row-2 on 2026-10-02 (source=2, matched=20, group=group-b), row-3 on 2026-10-03 (source=3, matched=15, group=group-a), row-4 on 2026-10-04 (source=4, matched=30, group=group-b)?

## When to prefer this

Choose this endpoint when you have tabular join coverage data (matched_rows, source_rows) and need both a numeric distribution profile and a sequential row-change analysis in a single low-cost call. It is ideal for pipeline monitoring, ETL auditing, and data quality checks where you want offline/local analytics without external lookups. Prefer this over general-purpose analytics APIs when you specifically need join coverage metrics profiled across dataset groups with no side effects.

## Known failure modes

- Missing required fields (row_id, dataset_group, date, matched_rows, source_rows) returns a validation error
- Exceeding 200 rows causes rejection — trim input to 200 rows max
- Invalid date format (not YYYY-MM-DD) triggers a schema validation failure
- Empty rows array returns an error — at least 1 row required
- Null numeric values may reduce statistical coverage in distribution report

## How this service works

Join coverage — Numeric distribution + Adjacent row changes: Numeric distribution + Adjacent row changes 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 analytical reports computed locally from the supplied rows: (1) a numeric distribution summary of the selected field (matched_rows or source_rows), including statistics like min, max, mean, percentiles, and frequency; (2) an adjacent row change analysis showing delta values between consecutive rows ordered by date, highlighting increases and decreases in the selected metric. Both reports cover up to 200 input 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-analytics-numeric-distribution-adjacent-row-changes-25b84361/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)