# Competitor Supplied Prices — Adjacent Row Changes + Explicit Missing-Value Fill

> Competitor Supplied Prices — Adjacent Row Changes + Explicit Missing-Value Fill is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-19).

Analyzes competitor supplied price records to detect adjacent row changes and fill explicit missing values in list_price or package_quantity fields, returning two analytical reports for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-company-07-162?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-19
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/competitor-supplied-prices-adjacent-row-changes-explicit-missing-8cfe4cb6
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_hZ7d-yTGn08xM8wrEsp0k

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 competitor-supplied-prices-adjacent-row-changes-explicit-missing-8cfe4cb6 -d '<json body>'
```

Example prompt: Can you analyze these competitor price records — up to 200 rows with row_id, company_group, date, list_price, and package_quantity — to detect adjacent row changes and fill any missing list_price values using median imputation? I want both reports back.

## When to prefer this

Use this endpoint when you have locally supplied competitor pricing data (up to 200 rows) and need both row-to-row change detection and missing-value imputation in a single low-cost call. It is ideal for offline data cleaning and audit workflows where no live lookups or external predictions are needed. Choose this over generic data pipelines when your data fits the specific schema (row_id, company_group, date, list_price, package_quantity) and you want two bundled analytical reports for $0.01.

## Known failure modes

- Exceeding 200 rows causes a validation error
- Missing required fields (row_id, company_group, date) result in schema rejection
- Invalid date format (not YYYY-MM-DD) triggers pattern validation failure
- Field values outside ±1,000,000,000,000 are rejected
- Empty rows array returns an error
- Invalid method or field enum values are rejected

## How this service works

Competitor supplied prices — Adjacent row changes + Explicit missing-value fill: Adjacent row changes + Explicit missing-value fill for supplied competitor supplied prices records (list_price, package_quantity). 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: (1) an adjacent row change report highlighting where list_price or package_quantity values differ between consecutive rows, and (2) an explicit missing-value fill report showing which null values were replaced and with what imputed values (zero, mean, or median), based entirely on the supplied input 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",
     "list_price",
     "package_quantity"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "maxLength": 10
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "list_price": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "company_group": {
      "type": "string",
      "default": "",
      "maxLength": 80
     },
     "package_quantity": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "list_price": 10,
     "company_group": "group-a",
     "package_quantity": 1
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "list_price": 20,
     "company_group": "group-b",
     "package_quantity": 2
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "list_price": 15,
     "company_group": "group-a",
     "package_quantity": 3
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "list_price": 30,
     "company_group": "group-b",
     "package_quantity": 4
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "list_price",
    "package_quantity"
   ],
   "type": "string",
   "default": "list_price"
  },
  "method": {
   "enum": [
    "zero",
    "mean",
    "median"
   ],
   "type": "string",
   "default": "median"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/competitor-supplied-prices-adjacent-row-changes-explicit-missing-8cfe4cb6/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)