# Compositing Graphs — Adjacent Row Changes + Two-Measure Correlation

> Compositing Graphs — 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 2026-10-17).

Analyzes compositing graph records (node_count, render_seconds) by computing adjacent row changes and two-measure correlation across up to 200 rows in two independent reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-creative-09-158?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-17
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/compositing-graphs-adjacent-row-changes-two-measure-correlation-9d6b05f3
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_khgjIqZ1825ldO7-clewW

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 compositing-graphs-adjacent-row-changes-two-measure-correlation-9d6b05f3 -d '<json body>'
```

Example prompt: I have compositing graph records with node counts and render times — can you run an adjacent row change analysis and a two-measure correlation report on this data? Here are my rows: row-1 on 2026-10-01 with node_count 10 and render_seconds 1 (group-a), row-2 on 2026-10-02 with node_count 20 and render_seconds 2 (group-b), row-3 on 2026-10-03 with node_count 15 and render_seconds 3 (group-a). Use node_count as the primary field.

## When to prefer this

Choose this endpoint when you have compositing graph records with node_count and render_seconds fields and need both a sequential change analysis (adjacent row deltas) and a cross-measure correlation in a single API call. It is purpose-built for compositing pipeline data with asset group and date dimensions, and bundles two reports for a flat $0.01 USDC fee — making it cost-efficient compared to calling separate analysis endpoints.

## Known failure modes

- Fewer than 1 row supplied — minimum row count not met
- More than 200 rows supplied — exceeds maximum allowed
- Missing required fields (row_id, date, asset_group, node_count, render_seconds) on any row
- Invalid date format (must match YYYY-MM-DD pattern)
- Numeric values outside allowed range (-1e12 to 1e12)
- Payment not included or insufficient — x402 payment required at $0.01 USDC
- All null values for a measure — correlation or delta cannot be computed

## How this service works

Compositing graphs — Adjacent row changes + Two-measure correlation: Adjacent row changes + Two-measure correlation for supplied compositing graphs records (node_count, render_seconds). 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) an adjacent row changes series showing delta values between consecutive rows for the selected measure, and (2) a two-measure correlation report quantifying the statistical relationship between node_count and render_seconds across the supplied dataset. Both reports are computed locally with no external lookups.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/compositing-graphs-adjacent-row-changes-two-measure-correlation-9d6b05f3/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)