# Supplier Qualification — String Normalisation + Adjacent Row Changes

> Supplier Qualification — String Normalisation + 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 2026-11-02).

Analyzes up to 200 supplier qualification rows by performing string normalization and detecting adjacent row changes on checked_criteria or met_criteria fields, returning two analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-company-02-029?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-11-02
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/supplier-qualification-string-normalisation-adjacent-row-changes-a5608a34
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_lQ_uNwy1OjOmUL-52E1lM

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-adjacent-row-changes-a5608a34 -d '<json body>'
```

Example prompt: Can you run string normalization and adjacent row change detection on my supplier qualification records — I have 4 rows with checked_criteria values (10, 20, 15, 30) for groups group-a and group-b from October 2026, and I want to analyze the checked_criteria field?

## When to prefer this

Choose this endpoint when you need to batch-process supplier qualification records (up to 200 rows) and require both string normalization and adjacent row change detection in a single low-cost call. Ideal for procurement or supply chain analysts who want to clean and audit qualification data without external lookups or live data sources. Best suited when data is already collected and needs offline analytical processing across two report types simultaneously.

## Known failure modes

- More than 200 rows submitted — request rejected or truncated
- Missing required fields (row_id, company_group, date, checked_criteria, met_criteria) — validation error
- Invalid date format (must be YYYY-MM-DD) — schema validation failure
- Values outside numeric range (-1,000,000,000,000 to 1,000,000,000,000) — rejection
- Invalid field enum value (must be checked_criteria or met_criteria) — error
- Empty rows array — minimum 1 item required

## How this service works

Supplier qualification — String normalisation + Adjacent row changes: String normalisation + Adjacent row changes 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 independent analytical reports for the supplied rows: (1) a string normalization report for the selected field (checked_criteria or met_criteria), and (2) an adjacent row changes report highlighting where consecutive rows differ — both computed locally without 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
  },
  "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-string-normalisation-adjacent-row-changes-a5608a34/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)