# Schema Conformity Analytics — String Normalisation & Grouped Numeric Summary

> Schema Conformity Analytics — String Normalisation & Grouped Numeric Summary is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-14).

Runs two local analytical reports on schema conformity records: string normalisation of row/group identifiers and a grouped numeric summary of valid_records or checked_records values across up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-02-023?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-14
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/schema-conformity-analytics-string-normalisation-grouped-numeric-5d5ef575
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_dWjapcJvGfmg82w-IzW3F

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-string-normalisation-grouped-numeric-5d5ef575 -d '<json body>'
```

Example prompt: Can you run the string normalisation and grouped numeric summary reports on my schema conformity data? I have 4 rows — row-1 in group-a on 2026-10-01 with 10 valid and 1 checked, row-2 in group-b on 2026-10-02 with 20 valid and 2 checked, row-3 in group-a on 2026-10-03 with 15 valid and 3 checked, row-4 in group-b on 2026-10-04 with 30 valid and 4 checked — and I want the summary focused on valid_records.

## When to prefer this

Choose this endpoint when you need both string normalisation of dataset identifiers and grouped numeric aggregation of schema conformity metrics (valid_records or checked_records) in a single API call for up to 200 rows. It is ideal for data quality pipelines, governance audits, or batch analytics on conformity scan outputs where no external lookup, prediction, or live data is required. Prefer it over generic analytics tools when your data already follows the schema conformity record structure with row_id, dataset_group, date, valid_records, and checked_records fields.

## Known failure modes

- More than 200 rows submitted — request rejected or truncated
- Missing required fields (row_id, date, valid_records, checked_records) on any row — validation error
- date field does not match YYYY-MM-DD pattern — schema validation failure
- field enum value not one of valid_records or checked_records — rejected
- All numeric values are null — summary may return empty or degenerate statistics
- row_id exceeds 80 characters — schema validation error

## How this service works

Schema conformity — String normalisation + Grouped numeric summary: String normalisation + Grouped numeric summary 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 independent analytical reports: (1) a string normalisation report covering row_id and dataset_group fields, cleaning and standardising label formats; and (2) a grouped numeric summary aggregating the selected field (valid_records or checked_records) across dataset_group values, including counts, totals, and descriptive statistics — all computed locally with no external data 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"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/schema-conformity-analytics-string-normalisation-grouped-numeric-5d5ef575/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)