# Numeric Precision Comparisons — String Normalisation + Adjacent Row Changes

> Numeric Precision Comparisons — String Normalisation + Adjacent Row Changes is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-11-02).

Analyzes up to 200 rows of source/transformed numeric value pairs, producing two local analytical reports: string normalisation of numeric values and adjacent row change detection.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-20-029?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-11-02
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/numeric-precision-comparisons-string-normalisation-adjacent-row-changes-b36f6fde
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_O0Qt_BlVtozH0VakfFDKy

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-string-normalisation-adjacent-row-changes-b36f6fde -d '<json body>'
```

Example prompt: Can you run a string normalisation and adjacent row changes analysis on these 4 rows of source vs transformed values — row-1 on 2026-10-01 with source 10 and transformed 1 in group-a, row-2 on 2026-10-02 with source 20 and transformed 2 in group-b, row-3 on 2026-10-03 with source 15 and transformed 3 in group-a, and row-4 on 2026-10-04 with source 30 and transformed 4 in group-b — using source_value as the field?

## When to prefer this

Choose this endpoint when you need lightweight, cost-effective local computation on up to 200 rows of numeric source/transformed pairs — specifically for string normalisation and adjacent row change reports — without requiring external data lookups, predictions, or professional assessments. Ideal for ETL validation, data migration checks, or time-series step analysis within a single API call at $0.01 USDC for two bundled reports.

## Known failure modes

- Exceeding 200 rows returns a validation error
- Missing required fields (row_id, dataset_group, date, source_value, transformed_value) causes rejection
- Dates not matching YYYY-MM-DD pattern are rejected
- Numeric values outside ±1,000,000,000,000 are rejected
- Empty rows array is rejected
- Invalid field enum value (not source_value or transformed_value) causes error

## How this service works

Numeric precision comparisons — String normalisation + Adjacent row changes: String normalisation + Adjacent row changes for supplied numeric precision comparisons records (source_value, transformed_value). 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 analytical reports for the submitted rows: (1) a string normalisation report showing how numeric values are standardised in text form, and (2) an adjacent row changes report showing value differences between consecutive rows. Results are computed locally from the supplied data with no external lookups.

## 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-string-normalisation-adjacent-row-changes-b36f6fde/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)