# Schema Conformity — Numeric Interval Filter + Adjacent Row Changes

> Schema Conformity — Numeric Interval Filter + 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 2026-10-18).

Filters schema conformity rows by a numeric interval on valid_records or checked_records, then reports adjacent row-to-row changes across up to 200 records in two independent analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-02-127?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-18
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/schema-conformity-numeric-interval-filter-adjacent-row-changes-4e94221c
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_-pdAzgIqI-DKGM_uhELrz

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-adjacent-row-changes-4e94221c -d '<json body>'
```

Example prompt: Filter my schema conformity dataset by valid_records between 5 and 100, and also show me how valid_records changed between adjacent rows — I have about 50 rows with date, row_id, dataset_group, valid_records, and checked_records.

## When to prefer this

Choose this endpoint when you have pre-collected schema conformity records (valid_records, checked_records) and need both a numeric range filter and an adjacent row change report in a single call, without needing live data lookup, predictions, or external data enrichment. It is particularly suited for data quality pipelines where you want to isolate records within acceptable bounds and simultaneously audit sequential row shifts.

## Known failure modes

- Rows array missing or empty — minimum 1 row required
- Row missing required fields (row_id, dataset_group, date, valid_records, checked_records) — schema validation error
- Date field does not match YYYY-MM-DD pattern — rejected
- More than 200 rows submitted — exceeds maximum
- Minimum greater than maximum — may return empty interval filter results
- Payment of 0.01 USDC not completed — 402 response blocking access

## How this service works

Schema conformity — Numeric interval filter + Adjacent row changes: Numeric interval filter + Adjacent row changes 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

Returns two reports: (1) rows whose specified field (valid_records or checked_records) falls within the supplied minimum–maximum interval, and (2) adjacent row change analysis showing the difference in that field between consecutive rows — all computed locally against the supplied data, up to 200 rows.

## 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-adjacent-row-changes-4e94221c/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)