# Price Basket Observations — Record Quality Audit & Numeric Interval Filter

> Price Basket Observations — Record Quality Audit & Numeric Interval Filter is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-27).

Audits data quality and filters by numeric interval for up to 200 rows of price basket observations (item_price, quantity_weight), returning two analytical reports per call.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-economics-07-008?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-27
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/price-basket-observations-record-quality-audit-numeric-interval-filter-00b32cca
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_C04eMqatEvhFAJz2fbu7Z

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 price-basket-observations-record-quality-audit-numeric-interval-filter-00b32cca -d '<json body>'
```

Example prompt: Can you run a record quality audit and numeric interval filter on my price basket observations? I have 50 rows with item_price and quantity_weight fields — filter item_price between 0 and 500, and flag any quality issues in the records.

## When to prefer this

Choose this endpoint when you need a lightweight, low-cost ($0.01 USDC) dual-report check on price basket observation data — specifically when you want both a data quality audit and a numeric range filter in a single call for up to 200 rows. Prefer this over general-purpose data validation tools when your data specifically contains item_price and quantity_weight fields with region and date context, and you do not need live lookups, predictive analytics, or external data enrichment.

## Known failure modes

- Submitting more than 200 rows returns a validation error
- Missing required fields (row_id, region, date, item_price, or quantity_weight) causes row-level rejection
- Invalid date format (non-YYYY-MM-DD) triggers a pattern validation error
- Specifying a minimum greater than maximum may yield an empty interval filter result
- Null values in item_price or quantity_weight are flagged in the quality audit but may not cause a call failure
- Invalid field enum value (anything other than item_price or quantity_weight) returns a schema error

## How this service works

Price basket observations — Record quality audit + Numeric interval filter: Record quality audit + Numeric interval filter for supplied price basket observations records (item_price, quantity_weight). 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) a record quality audit identifying data issues such as nulls, malformed values, or out-of-range entries across the supplied rows; and (2) a numeric interval filter report showing which rows for the selected field (item_price or quantity_weight) fall within or outside the specified minimum-maximum range. No live data or external lookups are involved — all analysis is local to the submitted data.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "rows": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "row_id",
     "region",
     "date",
     "item_price",
     "quantity_weight"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "maxLength": 10
     },
     "region": {
      "type": "string",
      "default": "",
      "maxLength": 80
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "item_price": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "quantity_weight": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "region": "group-a",
     "row_id": "row-1",
     "item_price": 10,
     "quantity_weight": 1
    },
    {
     "date": "2026-10-02",
     "region": "group-b",
     "row_id": "row-2",
     "item_price": 20,
     "quantity_weight": 2
    },
    {
     "date": "2026-10-03",
     "region": "group-a",
     "row_id": "row-3",
     "item_price": 15,
     "quantity_weight": 3
    },
    {
     "date": "2026-10-04",
     "region": "group-b",
     "row_id": "row-4",
     "item_price": 30,
     "quantity_weight": 4
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "item_price",
    "quantity_weight"
   ],
   "type": "string",
   "default": "item_price"
  },
  "maximum": {
   "type": "number",
   "default": 100,
   "maximum": 1000000000000,
   "minimum": -1000000000000
  },
  "minimum": {
   "type": "number",
   "default": 0,
   "maximum": 1000000000000,
   "minimum": -1000000000000
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/price-basket-observations-record-quality-audit-numeric-interval-filter-00b32cca/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)