# Join Coverage Analytics: Numeric Interval Filter + Adjacent Row Changes

> Join Coverage Analytics: Numeric Interval Filter + 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 2026-10-23).

Analyzes join coverage records (matched_rows, source_rows) by applying a numeric interval filter and detecting adjacent row changes across up to 200 rows in two independent reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-09-127?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-numeric-interval-filter-adjacent-row-changes-0f62dbbf
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_4OTtMVuW6Oqn3p8a-880L

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-interval-filter-adjacent-row-changes-0f62dbbf -d '<json body>'
```

Example prompt: Can you analyze my join coverage data — I have 4 rows for dataset groups 'group-a' and 'group-b' from 2026-10-01 to 2026-10-04 — and run both the numeric interval filter (minimum 0, maximum 100) and adjacent row changes report on the matched_rows field?

## When to prefer this

Choose this endpoint when you have join coverage tabular data (matched_rows and source_rows per date/group) and need both a numeric range filter and an adjacent-row change detection report in a single call. It is ideal for data engineers and analysts monitoring ETL join quality, data reconciliation pipelines, or coverage drift over time. Prefer this over general-purpose analytics tools when you want two bundled local analytical reports at low cost ($0.01 USDC) without any external data lookups or ML predictions.

## Known failure modes

- Input array exceeds 200 rows — request rejected
- Missing required fields (row_id, date, dataset_group, matched_rows, source_rows) on any row — validation error
- Date fields not matching YYYY-MM-DD format — schema validation failure
- Minimum value greater than maximum value — may produce empty filter results
- Numeric values outside allowed range (±1,000,000,000,000) — schema rejection
- Empty rows array — rejected due to minItems:1 constraint

## How this service works

Join coverage — Numeric interval filter + Adjacent row changes: Numeric interval filter + 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 independent analytical reports for the supplied join coverage rows: (1) a numeric interval filter report identifying which rows have the selected field (matched_rows or source_rows) within the specified minimum/maximum range, and (2) an adjacent row changes report highlighting where consecutive rows show a change in the selected field value. Results cover up to 200 input rows with no external lookups or predictions.

## 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"
  },
  "maximum": {
   "type": "number",
   "default": 100,
   "maximum": 1000000000000,
   "minimum": -1000000000000
  },
  "minimum": {
   "type": "number",
   "default": 0,
   "maximum": 1000000000000,
   "minimum": -1000000000000
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/join-coverage-analytics-numeric-interval-filter-adjacent-row-changes-0f62dbbf/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)