# Schema Conformity Analytics: Category Frequencies + Base-100 Series

> Schema Conformity Analytics: Category Frequencies + Base-100 Series is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-16).

Computes category-frequency distributions and base-100 index series for schema conformity records (valid_records, checked_records) across up to 200 rows, returning two independent analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-02-105?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-16
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/schema-conformity-analytics-category-frequencies-base-100-series-d8680cdf
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_fcFj8zZcVgp_e1aipABEe

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-analytics-category-frequencies-base-100-series-d8680cdf -d '<json body>'
```

Example prompt: I have 150 rows of schema conformity data with valid_records and checked_records per dataset group — can you compute the category frequencies and a base-100 index series for the valid_records field, using row 0 as the base?

## When to prefer this

Choose this endpoint when you have schema conformity record data (valid_records, checked_records) already on hand and need two complementary analytical views — category frequency distributions and a normalized base-100 trend series — computed in a single low-cost call. Ideal for data quality monitoring workflows where you want both group-level summaries and temporal indexing without needing external lookups or predictions.

## Known failure modes

- Input array is empty or exceeds 200 rows — validation error returned
- Invalid date format not matching YYYY-MM-DD pattern — schema validation failure
- base_index out of range (>= number of rows supplied) — index error
- Null values in valid_records or checked_records may affect index calculation
- Missing required fields (row_id, dataset_group, date) cause item-level rejection

## How this service works

Schema conformity — Category frequencies + Base-100 series: Category frequencies + Base-100 series 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 analytical reports: (1) a category frequency table showing how often each dataset_group appears and the distribution of the selected field's values, and (2) a base-100 index series showing relative changes in the selected field (valid_records or checked_records) normalized to the specified base row. 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"
  },
  "base_index": {
   "type": "integer",
   "default": 0,
   "maximum": 199,
   "minimum": 0
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/schema-conformity-analytics-category-frequencies-base-100-series-d8680cdf/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)