# Supplier Qualification — Adjacent Row Changes + Two-Measure Correlation

> Supplier Qualification — 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 2026-10-15).

Computes adjacent row delta analysis and Pearson/rank correlation between checked_criteria and met_criteria for up to 200 supplier qualification records.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-company-02-158?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/supplier-qualification-adjacent-row-changes-two-measure-correlation-aaa9fdfd
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_rRUBGxg2syWT_WyAqglpF

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 supplier-qualification-adjacent-row-changes-two-measure-correlation-aaa9fdfd -d '<json body>'
```

Example prompt: Can you run adjacent row change analysis and a two-measure correlation between checked_criteria and met_criteria on my supplier qualification data? I have about 50 rows with company groups and dates from October 2026 — I want to see how scores shift row by row and whether the two metrics move together.

## When to prefer this

Choose this endpoint when you have tabular supplier qualification data with checked_criteria and met_criteria columns and need both a sequential row-delta analysis and a bivariate correlation report in a single API call at low cost. It is particularly suited for procurement analysts who want to detect drift in supplier pass rates and measure whether evaluation rigor (checked_criteria) correlates with outcomes (met_criteria) without sending data to external ML or prediction services.

## Known failure modes

- Input array exceeds 200 rows — request rejected
- Missing required fields (row_id, date, company_group) — validation error
- Invalid date format not matching YYYY-MM-DD pattern — parse error
- Fewer than 2 rows provided — insufficient data for adjacent change or correlation computation
- Numeric values outside allowed range (±1,000,000,000,000) — schema validation failure
- Invalid field enum value (not checked_criteria or met_criteria) — rejected

## How this service works

Supplier qualification — Adjacent row changes + Two-measure correlation: Adjacent row changes + Two-measure correlation for supplied supplier qualification records (checked_criteria, met_criteria). 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 changes report showing delta values between consecutive rows for the selected field (checked_criteria or met_criteria), and (2) a two-measure correlation report quantifying the statistical relationship between checked_criteria and met_criteria across all supplied rows. Analysis covers up to 200 rows using local engines with no external data lookups.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/supplier-qualification-adjacent-row-changes-two-measure-correlation-aaa9fdfd/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)