# Schema Conformity — Numeric Interval Filter + Date by Category Pivot

> Schema Conformity — Numeric Interval Filter + 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 2026-10-22).

Filters schema conformity rows by a numeric interval on valid_records or checked_records, then pivots dates by dataset_group category — two analytical reports in one call.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-02-133?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-22
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/schema-conformity-numeric-interval-filter-date-by-category-pivot-4a512787
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_VgtJ6yCbTBiG3bjberaLp

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 schema-conformity-numeric-interval-filter-date-by-category-pivot-4a512787 -d '<json body>'
```

Example prompt: Run two reports on my schema conformity data: filter the rows where valid_records is between 10 and 500, and also pivot the dates by dataset_group category — here are my 50 rows with row_id, dataset_group, date, valid_records, and checked_records fields.

## When to prefer this

Choose this endpoint when you need both a numeric range filter and a date-by-category pivot on schema conformity data (valid_records, checked_records) in a single cheap call. It is ideal for data quality pipelines where you want to isolate records within acceptable bounds and simultaneously see temporal category breakdowns. Prefer it over general-purpose analytics tools when your data is already structured with row_id, dataset_group, date, valid_records, and checked_records fields and you want two focused reports without external computation.

## Known failure modes

- Input rows array is empty or exceeds 200 items — request rejected
- minimum value greater than maximum value — invalid interval, likely returns empty filter result or error
- Required row fields (row_id, date, dataset_group, valid_records, checked_records) missing or malformed — validation error
- Date strings not matching YYYY-MM-DD pattern — schema validation failure
- numeric fields out of allowed range (±1 trillion) — rejected by schema
- Payment of 0.01 USDC not completed via x402 protocol — 402 Payment Required response

## How this service works

Schema conformity — Numeric interval filter + Date by category pivot: Numeric interval filter + Date by category pivot for supplied schema conformity records (valid_records, checked_records). 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 returned together: (1) a subset of the input rows where the chosen numeric field (valid_records or checked_records) falls within the specified [minimum, maximum] interval, and (2) a pivot table of dates cross-tabulated by dataset_group category — both computed locally from the supplied data with no external lookups.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "rows": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "row_id",
     "dataset_group",
     "date",
     "valid_records",
     "checked_records"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "maxLength": 10
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "dataset_group": {
      "type": "string",
      "default": "",
      "maxLength": 80
     },
     "valid_records": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "checked_records": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "dataset_group": "group-a",
     "valid_records": 10,
     "checked_records": 1
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "dataset_group": "group-b",
     "valid_records": 20,
     "checked_records": 2
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "dataset_group": "group-a",
     "valid_records": 15,
     "checked_records": 3
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "dataset_group": "group-b",
     "valid_records": 30,
     "checked_records": 4
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "valid_records",
    "checked_records"
   ],
   "type": "string",
   "default": "valid_records"
  },
  "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/schema-conformity-numeric-interval-filter-date-by-category-pivot-4a512787/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)