# Numeric Precision Comparisons — Duplicate Key Report + Adjacent Row Changes

> Numeric Precision Comparisons — Duplicate Key Report + 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 2026-10-15).

Analyzes up to 200 rows of source/transformed numeric value pairs to produce two local analytical reports: a duplicate key report and an adjacent row changes report.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-20-062?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-duplicate-key-report-adjacent-row-changes-8a2879a2
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_8rLVZYfRj6UMxDIPtQIzp

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-duplicate-key-report-adjacent-row-changes-8a2879a2 -d '<json body>'
```

Example prompt: I have up to 200 rows of source and transformed numeric values with row IDs, dataset groups, and dates — can you run a duplicate key report and adjacent row changes report on them, analyzing the source_value field?

## When to prefer this

Choose this endpoint when you need fast, local analytical reports on a batch of numeric source/transformed value pairs — specifically duplicate key detection and adjacent row change detection — without requiring external data lookups, ML predictions, or professional assessments. Ideal for data quality checks in ETL pipelines, transformation audits, and pre-reporting validation where you have up to 200 rows and need two structured reports in a single low-cost call.

## Known failure modes

- Input rows exceed 200 item limit — request rejected
- Missing required fields (row_id, dataset_group, date, source_value, transformed_value) on any row — validation error
- Date field does not match YYYY-MM-DD pattern — schema validation failure
- Numeric values outside allowed range (-1,000,000,000,000 to 1,000,000,000,000) — rejected
- Invalid field enum value (must be 'source_value' or 'transformed_value') — error
- Empty rows array — rejected due to minItems:1 constraint

## How this service works

Numeric precision comparisons — Duplicate key report + Adjacent row changes: Duplicate key report + 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 independent analytical reports: (1) a duplicate key report identifying row_ids that appear more than once in the supplied dataset, and (2) an adjacent row changes report showing where consecutive rows differ in the selected numeric field (source_value or transformed_value). Both reports 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-duplicate-key-report-adjacent-row-changes-8a2879a2/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)