# Numeric Precision Comparisons — Record Quality Audit, String Normalisation & Duplicate Key Report

> Numeric Precision Comparisons — Record Quality Audit, String Normalisation & Duplicate Key Report is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-15).

Runs three local analytical reports (record quality audit, string normalisation, and duplicate key detection) on supplied numeric source-vs-transformed value pairs, up to 200 rows per call.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-20-192?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-15
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/numeric-precision-comparisons-record-quality-audit-string-3b1ab94a
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_UXXmYNcRD5K8DCBGh2u0F

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 numeric-precision-comparisons-record-quality-audit-string-3b1ab94a -d '<json body>'
```

Example prompt: Can you run the three data quality reports — record quality audit, string normalisation, and duplicate key check — on these 150 rows of source-to-transformed numeric values from my ETL pipeline? The rows have row_id, dataset_group, date, source_value, and transformed_value fields.

## When to prefer this

Choose this endpoint when you need three bundled analytical reports (quality audit, string normalisation, duplicate detection) on a batch of numeric source-vs-transformed records without requiring any external data lookups, live predictions, or professional assessments. It is ideal for ETL validation, data pipeline QA, and pre-load data checks where all data is self-contained and up to 200 rows per call is sufficient.

## Known failure modes

- Rows array exceeds 200 items — request rejected
- Missing required fields (row_id, dataset_group, date, source_value, transformed_value) — validation error
- Date field does not match YYYY-MM-DD pattern — schema validation failure
- Numeric values outside ±1,000,000,000,000 range — validation error
- Empty rows array — minimum item constraint violation

## How this service works

Numeric precision comparisons — Record quality audit + String normalisation + Duplicate key report: Record quality audit + String normalisation + Duplicate key report for supplied numeric precision comparisons records (source_value, transformed_value). 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

Three independent analytical reports returned for the submitted rows: (1) a record quality audit flagging anomalies or issues in the numeric records, (2) a string normalisation report on value representations, and (3) a duplicate key report identifying repeated row_id or key combinations across the submitted dataset.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "rows": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "row_id",
     "dataset_group",
     "date",
     "source_value",
     "transformed_value"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "maxLength": 10
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "source_value": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "dataset_group": {
      "type": "string",
      "default": "",
      "maxLength": 80
     },
     "transformed_value": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "source_value": 10,
     "dataset_group": "group-a",
     "transformed_value": 1
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "source_value": 20,
     "dataset_group": "group-b",
     "transformed_value": 2
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "source_value": 15,
     "dataset_group": "group-a",
     "transformed_value": 3
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "source_value": 30,
     "dataset_group": "group-b",
     "transformed_value": 4
    }
   ],
   "maxItems": 200,
   "minItems": 1
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/numeric-precision-comparisons-record-quality-audit-string-3b1ab94a/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)