# Sampling Observations — Numeric Distribution + Adjacent Row Changes

> Sampling Observations — 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 2026-10-15).

Analyzes up to 200 sampling observation rows (sample_value/sample_weight) producing two local analytical reports: a numeric distribution summary and an adjacent row change analysis.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-15-077?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-15
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/sampling-observations-numeric-distribution-adjacent-row-changes-5a4dadb1
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_3AD-_9KeJsdsUa3xAiFOS

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 sampling-observations-numeric-distribution-adjacent-row-changes-5a4dadb1 -d '<json body>'
```

Example prompt: Can you run a numeric distribution and adjacent row change analysis on my sampling observations? I have 4 rows — row-1 on 2026-10-01 in group-a with sample_value 10 and weight 1, row-2 on 2026-10-02 in group-b with value 20 and weight 2, row-3 on 2026-10-03 in group-a with value 15 and weight 3, and row-4 on 2026-10-04 in group-b with value 30 and weight 4 — analyze the sample_value field.

## When to prefer this

Choose this endpoint when you need both a numeric distribution summary and consecutive row-change analysis on sampling observation data (up to 200 rows) in a single $0.01 call. It is ideal when your data already includes sample weights and you want two complementary statistical perspectives — spread and sequential delta — without any external API calls, live lookups, or professional assessments. Prefer it over single-report endpoints when you need both distribution and adjacency-change insights bundled cost-efficiently.

## Known failure modes

- Input array is empty or missing (minItems:1 violated) — validation error returned
- More than 200 rows supplied (maxItems:200 violated) — request rejected
- Date field does not match YYYY-MM-DD pattern — validation error
- sample_value or sample_weight outside ±1,000,000,000,000 range — validation error
- field enum value not 'sample_value' or 'sample_weight' — validation error
- Payment of 0.01 USDC not completed via x402 protocol — 402 response, no report generated

## How this service works

Sampling observations — Numeric distribution + Adjacent row changes: Numeric distribution + Adjacent row changes for supplied sampling observations records (sample_value, sample_weight). 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

Two independent analytical reports: (1) a numeric distribution report covering statistical spread metrics (e.g. min, max, mean, percentiles, histogram buckets) for the chosen field across all supplied rows, and (2) an adjacent row changes report showing the difference between each consecutive pair of rows ordered as supplied, highlighting step changes in the selected field. All computation is performed locally with no external data lookups.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/sampling-observations-numeric-distribution-adjacent-row-changes-5a4dadb1/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)