# Validation Rule Results — String Normalisation + Date by Category Pivot

> Validation Rule Results — String Normalisation + 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 2026-10-11).

Applies string normalisation and a date-by-category pivot analysis to up to 200 validation rule result records (passed_rules, total_rules), returning two independent analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-08-035?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-string-normalisation-date-by-category-pivot-502f80ae
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_2D_EPLh497kRXxxhDUg_C

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-string-normalisation-date-by-category-pivot-502f80ae -d '<json body>'
```

Example prompt: I have up to 200 rows of validation rule results with fields like row_id, dataset_group, date, passed_rules, and total_rules — can you run string normalisation and a date-by-category pivot on the passed_rules field and give me both reports?

## When to prefer this

Choose this endpoint when you need both string normalisation and a date-by-category pivot on validation rule result data (passed_rules / total_rules) in a single call for up to 200 rows. It is well-suited for data quality reporting pipelines where you want two complementary views — cleaned string data and a time-group breakdown — without external lookups or predictions.

## Known failure modes

- More than 200 rows submitted — request rejected with validation error
- Missing required fields (row_id, dataset_group, date, passed_rules, total_rules) — row-level or request-level error
- Invalid date format (not YYYY-MM-DD) — pattern validation failure
- Numeric field values outside allowed range — validation error
- Empty rows array — minimum items constraint failure

## How this service works

Validation rule results — String normalisation + Date by category pivot: String normalisation + Date by category pivot for supplied validation rule results records (passed_rules, total_rules). 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: (1) a string-normalised view of the input validation rule result records, and (2) a date-by-category pivot table aggregating the selected numeric field (passed_rules or total_rules) by date and dataset_group, covering up to 200 input rows.

## 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"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/validation-rule-results-string-normalisation-date-by-category-pivot-502f80ae/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)