# Numeric Precision Comparisons — Category Frequencies & Adjacent Row Changes

> Numeric Precision Comparisons — Category Frequencies & 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 user-supplied numeric pairs (source_value, transformed_value) to produce two reports: category frequency distributions and adjacent-row delta changes, up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-20-104?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-category-frequencies-adjacent-row-changes-1b0cd3ef
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_tCilrBirzN3fQlQSWItM_

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-category-frequencies-adjacent-row-changes-1b0cd3ef -d '<json body>'
```

Example prompt: Analyze these 4 rows of source and transformed numeric values — I want both a category frequency breakdown and adjacent row change report for the source_value field: row-1 group-a 2026-10-01 source=10 transformed=1, row-2 group-b 2026-10-02 source=20 transformed=2, row-3 group-a 2026-10-03 source=15 transformed=3, row-4 group-b 2026-10-04 source=30 transformed=4.

## When to prefer this

Choose this endpoint when you have tabular numeric data with source and transformed value pairs and need two specific offline analytical outputs — category frequency distributions and consecutive-row change detection — without any external data lookup, prediction, or live enrichment. Ideal for ETL validation, data quality auditing, and precision transformation review on datasets up to 200 rows. Prefer this over general-purpose analytics tools when you want a lightweight, low-cost ($0.01 USDC) dual-report computation on supplied data only.

## Known failure modes

- More than 200 rows submitted — request rejected with validation error
- Missing required fields (row_id, dataset_group, date, source_value, transformed_value) — schema validation failure
- Date field not in YYYY-MM-DD format — pattern validation error
- Numeric values outside ±1,000,000,000,000 range — schema bounds error
- Empty rows array — minItems validation failure
- Invalid field enum value (not source_value or transformed_value) — enum validation error

## How this service works

Numeric precision comparisons — Category frequencies + Adjacent row changes: Category frequencies + 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

Returns two independent analytical reports for up to 200 supplied rows: (1) a category frequency breakdown showing how often each numeric precision category appears in the selected field, and (2) an adjacent row change report showing the delta between consecutive rows, grouped by dataset_group and ordered by date.

## 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-category-frequencies-adjacent-row-changes-1b0cd3ef/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)