# Numeric Precision Comparisons — Record Quality Audit + String Normalisation + Numeric Distribution

> Numeric Precision Comparisons — Record Quality Audit + String Normalisation + Numeric Distribution 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 independent analytical reports (record quality audit, string normalisation, and numeric distribution) on up to 200 rows of numeric source/transformed value pairs, entirely via local engines with no external lookups.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-20-193?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-e73474dd
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_6h-wcPuF_mcb6MOaBcfIm

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-e73474dd -d '<json body>'
```

Example prompt: Can you run the record quality audit, string normalisation, and numeric distribution reports on these 50 rows of my ETL output — the source_value and transformed_value fields are the ones I care about, grouped by 'group-a' and 'group-b'?

## When to prefer this

Choose this endpoint when you need three bundled data quality reports — quality audit, string normalisation, and numeric distribution — on a batch of numeric comparison rows (source vs transformed) at low cost ($0.01 for all three). Ideal for ETL validation, data migration checks, and numeric pipeline auditing where no live external data or predictive models are needed. Prefer this over single-report endpoints when all three report types are relevant to your batch.

## Known failure modes

- Exceeding 200 rows causes rejection — batch must be split
- Invalid date format (not YYYY-MM-DD) triggers schema validation error
- Numeric values outside ±1,000,000,000,000 range are rejected
- Empty rows array returns an error
- Missing required fields (row_id, dataset_group, date) cause validation failure
- Non-numeric values in source_value or transformed_value fields fail schema checks

## How this service works

Numeric precision comparisons — Record quality audit + String normalisation + Numeric distribution: Record quality audit + String normalisation + Numeric distribution 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

Returns three independent reports per call: (1) a record quality audit flagging nulls, anomalies, and completeness issues; (2) a string normalisation report on the value fields; and (3) a numeric distribution summary (min, max, mean, percentiles, spread) — all computed locally from the supplied rows with no external data sources.

## 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
  },
  "field": {
   "enum": [
    "source_value",
    "transformed_value"
   ],
   "type": "string",
   "default": "source_value"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/numeric-precision-comparisons-record-quality-audit-string-e73474dd/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)