# Supplier Qualification — String Normalisation + Two-Measure Correlation

> Supplier Qualification — String Normalisation + 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 2026-11-03).

Normalises string fields and computes correlation between checked_criteria and met_criteria across up to 200 supplier qualification rows, producing two independent analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-company-02-033?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-11-03
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/supplier-qualification-string-normalisation-two-measure-correlation-0d6d5d0c
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_sPzIxO8GI4--STUYuC_J2

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-string-normalisation-two-measure-correlation-0d6d5d0c -d '<json body>'
```

Example prompt: Analyse my supplier qualification records — I have 4 rows with company groups 'group-a' and 'group-b', dates from 2026-10-01 to 2026-10-04, checked_criteria values of 10, 20, 15, 30, and met_criteria values of 1, 2, 3, 4 — normalise the strings and give me a correlation report on those two measures.

## When to prefer this

Choose this endpoint when you have a batch of supplier qualification records (up to 200 rows) and need both string normalisation and a two-measure correlation between checked and met criteria in a single low-cost call ($0.01 USDC). It is purely analytical with no external lookups, making it deterministic and fast. Prefer it over general-purpose analytics tools when the data fits the specific schema (row_id, company_group, date, checked_criteria, met_criteria) and you need two bundled reports from a single payment.

## Known failure modes

- Rows array empty or missing — minimum 1 row required
- More than 200 rows submitted — exceeds maxItems limit
- Invalid date format — must match YYYY-MM-DD pattern
- row_id missing or empty — required field with minLength 1
- checked_criteria or met_criteria out of numeric bounds (±1,000,000,000,000)
- Malformed JSON body — schema validation failure
- Payment not included or insufficient — x402 payment required

## How this service works

Supplier qualification — String normalisation + Two-measure correlation: String normalisation + 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

Two independent analytical reports covering: (1) string normalisation results for the company_group and related text fields across the submitted rows, and (2) a correlation analysis between the checked_criteria and met_criteria numeric measures across all submitted rows — all computed locally with no external lookups or predictions.

## 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
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/supplier-qualification-string-normalisation-two-measure-correlation-0d6d5d0c/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)