# Supplier Qualification — Numeric Distribution + Date by Category Pivot

> Supplier Qualification — Numeric Distribution + Date by Category Pivot 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).

Runs two local analytical reports on supplier qualification data: a numeric distribution of checked/met criteria and a date-by-category pivot, for up to 200 supplied rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-company-02-083?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-numeric-distribution-date-by-category-pivot-1dd9d489
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_ql7BNqL9rWf2OKlCILHlH

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-numeric-distribution-date-by-category-pivot-1dd9d489 -d '<json body>'
```

Example prompt: Can you analyze my supplier qualification records for groups A and B — I have 4 rows with dates from 2026-10-01 to 2026-10-04, checked_criteria values of 10, 20, 15, and 30, and met_criteria of 1, 2, 3, and 4 — and give me both a numeric distribution and a date-by-category pivot for the checked_criteria field?

## When to prefer this

Choose this endpoint when you have up to 200 rows of supplier qualification records with checked_criteria and met_criteria numeric fields and need both a numeric distribution and a date-by-category pivot in a single $0.01 USDC call. Prefer it over general BI tools when you want a lightweight, payment-gated analytical summary without setting up a full data pipeline.

## Known failure modes

- Missing required fields (row_id, company_group, date, checked_criteria, or met_criteria) cause validation errors
- Date values not matching YYYY-MM-DD pattern are rejected
- Exceeding 200 rows returns an error
- Numeric values outside ±1,000,000,000,000 are rejected
- Empty rows array is rejected (minItems: 1)
- Invalid field enum value (must be 'checked_criteria' or 'met_criteria') causes error

## How this service works

Supplier qualification — Numeric distribution + Date by category pivot: Numeric distribution + Date by category pivot 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 analytical reports derived from the supplied rows: (1) a numeric distribution report showing statistical spread of the selected numeric field (checked_criteria or met_criteria), and (2) a date-by-category pivot that cross-tabulates values by date and company_group. All computation is performed locally on the supplied data with no external 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-numeric-distribution-date-by-category-pivot-1dd9d489/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)