# Join Coverage Analytics: Trailing Mean Series + Adjacent Row Changes

> Join Coverage Analytics: Trailing Mean Series + 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).

Computes trailing moving-average series and adjacent row-to-row delta changes for join coverage metrics (matched_rows and source_rows) across up to 200 supplied data rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-09-146?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-trailing-mean-series-adjacent-row-changes-c74d8b37
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_GrKMPH38ugDyA0jKug2rp

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-trailing-mean-series-adjacent-row-changes-c74d8b37 -d '<json body>'
```

Example prompt: Can you run trailing mean and adjacent row change analysis on my join coverage data? I have rows with matched_rows and source_rows across groups A and B from October 2026 — analyze the matched_rows field with a window size of 3.

## When to prefer this

Choose this endpoint when you have pre-collected join coverage records (matched_rows, source_rows) and need both a rolling/trailing mean time series and adjacent delta analysis in a single call for up to 200 rows, without needing live data lookups or external predictions. It is especially suitable for data engineers auditing ETL join quality over time, or analysts building QA dashboards on coverage metrics.

## Known failure modes

- Fewer than 1 row supplied — validation error
- More than 200 rows supplied — rejected with max-items error
- Window size larger than number of supplied rows — may yield sparse or empty trailing mean results
- Invalid date format (not YYYY-MM-DD) — schema validation error
- Missing required fields (row_id, dataset_group, date, matched_rows, source_rows) — validation error
- Null numeric values in the selected field — may produce null/undefined entries in the output series

## How this service works

Join coverage — Trailing mean series + Adjacent row changes: Trailing mean series + 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: (1) a trailing mean series computed over the specified window for the chosen field (matched_rows or source_rows), and (2) adjacent row-to-row change values for the same field — both derived purely from the supplied row data without any 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"
  },
  "window": {
   "type": "integer",
   "default": 2,
   "maximum": 200,
   "minimum": 2
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/join-coverage-analytics-trailing-mean-series-adjacent-row-changes-c74d8b37/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)