# Validation Rule Results Analytics — Record Quality Audit, String Normalisation & Numeric Interval Filter

> Validation Rule Results Analytics — Record Quality Audit, String Normalisation & 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 2026-10-11).

Performs three analytical reports on validation rule result records: record quality audit, string normalisation, and numeric interval filtering of passed_rules/total_rules fields.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-08-197?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-11
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/validation-rule-results-analytics-record-quality-audit-string-6d974e33
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_aIlkfTSGMpA-t7i3auC1I

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 validation-rule-results-analytics-record-quality-audit-string-6d974e33 -d '<json body>'
```

Example prompt: Can you run a quality audit, string normalisation, and numeric interval filter on my validation rule results? I have rows with dataset_group, date, passed_rules, and total_rules fields — focus on the passed_rules field and filter for values between 0 and 100.

## When to prefer this

Choose this endpoint when you need a combined record quality audit, string normalisation, and numeric interval filter on validation rule result data (passed_rules/total_rules) in a single call. It is ideal for batch data quality checks on up to 200 rows without any external API calls or live lookups. Prefer this over generic data tools when you specifically track rule compliance metrics by dataset group and need all three analytical reports at the cost of a single $0.01 USDC call.

## Known failure modes

- Fewer than 1 or more than 200 rows submitted — rejected with validation error
- Missing required fields (row_id, dataset_group, date, passed_rules, total_rules) on any row — schema validation failure
- Date field not matching YYYY-MM-DD pattern — rejected
- Minimum value greater than maximum value — may produce empty interval filter results
- Null numeric values for passed_rules or total_rules — may affect numeric filter and audit reports
- Invalid field enum value (not passed_rules or total_rules) — schema rejection

## How this service works

Validation rule results — Record quality audit + String normalisation + Numeric interval filter: Record quality audit + String normalisation + Numeric interval filter for supplied validation rule results records (passed_rules, total_rules). Up to 200 rows; 3 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 3 supplied-data reports for up to 200 rows.

## Output

Returns three independent analytical reports for the supplied rows: (1) a record quality audit flagging completeness and consistency issues, (2) string normalisation output for text fields like dataset_group, and (3) a numeric interval filter report identifying rows where the selected field (passed_rules or total_rules) falls within the specified min/max range. All processing is local with no external lookups.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "rows": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "row_id",
     "dataset_group",
     "date",
     "passed_rules",
     "total_rules"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "maxLength": 10
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "total_rules": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "passed_rules": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "dataset_group": {
      "type": "string",
      "default": "",
      "maxLength": 80
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "total_rules": 1,
     "passed_rules": 10,
     "dataset_group": "group-a"
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "total_rules": 2,
     "passed_rules": 20,
     "dataset_group": "group-b"
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "total_rules": 3,
     "passed_rules": 15,
     "dataset_group": "group-a"
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "total_rules": 4,
     "passed_rules": 30,
     "dataset_group": "group-b"
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "passed_rules",
    "total_rules"
   ],
   "type": "string",
   "default": "passed_rules"
  },
  "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/validation-rule-results-analytics-record-quality-audit-string-6d974e33/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)