# Asset Coverage: Adjacent Row Changes + Two-Measure Correlation

> Asset Coverage: Adjacent Row Changes + Two-Measure Correlation 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).

Computes adjacent row-to-row changes and two-measure correlation for asset coverage data (known_assets, monitored_assets) across up to 200 rows in two bundled analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-security-10-158?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/asset-coverage-adjacent-row-changes-two-measure-correlation-dd820125
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_36dnGd9pUBRZaVGbQR0Fi

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 asset-coverage-adjacent-row-changes-two-measure-correlation-dd820125 -d '<json body>'
```

Example prompt: Analyze my asset coverage records for adjacent row changes and correlation between known_assets and monitored_assets — here are 50 rows with dates from 2026-10-01 onward, grouped into control groups A and B, and I want the field focus on known_assets.

## When to prefer this

Choose this endpoint when you have structured asset coverage tabular data (known_assets and monitored_assets) and need both sequential row-change detection and cross-measure correlation in a single low-cost call. Ideal for offline batch analysis of up to 200 rows without needing live data lookup, prediction, or external enrichment. Best suited when you already have the data locally and want fast, deterministic statistical outputs rather than real-time monitoring or professional assessment.

## Known failure modes

- Exceeding 200 rows results in rejection or truncation
- Missing required fields (row_id, date, control_group, known_assets, monitored_assets) causes validation error
- Invalid date format (non YYYY-MM-DD) triggers schema rejection
- Null values in both measure columns may reduce correlation validity
- Submitting fewer than 1 row returns an error
- Values outside ±1,000,000,000,000 range are rejected by schema

## How this service works

Asset coverage — Adjacent row changes + Two-measure correlation: Adjacent row changes + Two-measure correlation for supplied asset coverage records (known_assets, monitored_assets). 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: (1) an adjacent row change report showing delta values between consecutive rows for the selected field, and (2) a two-measure correlation report quantifying the statistical relationship between known_assets and monitored_assets across the supplied rows, with up to 200 rows processed per call.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "rows": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "row_id",
     "control_group",
     "date",
     "known_assets",
     "monitored_assets"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "maxLength": 10
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "known_assets": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "control_group": {
      "type": "string",
      "default": "",
      "maxLength": 80
     },
     "monitored_assets": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "known_assets": 10,
     "control_group": "group-a",
     "monitored_assets": 1
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "known_assets": 20,
     "control_group": "group-b",
     "monitored_assets": 2
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "known_assets": 15,
     "control_group": "group-a",
     "monitored_assets": 3
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "known_assets": 30,
     "control_group": "group-b",
     "monitored_assets": 4
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "known_assets",
    "monitored_assets"
   ],
   "type": "string",
   "default": "known_assets"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/asset-coverage-adjacent-row-changes-two-measure-correlation-dd820125/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)