# Numeric Precision Comparisons — Record Quality Audit + Category Frequencies

> Numeric Precision Comparisons — Record Quality Audit + Category Frequencies 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 pairs, producing a record quality audit report and a category frequency report using local analytical engines.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-20-006?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-category-frequencies-d6ca4937
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_elD5Ncm9w24tYyznbrpq1

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-category-frequencies-d6ca4937 -d '<json body>'
```

Example prompt: Can you run a quality audit and category frequency report on these numeric pairs — I have up to 200 rows with source values and their transformed counterparts, each tagged with a dataset group and date, and I need to see where the precision looks off and how the records break down by group?

## When to prefer this

Choose this endpoint when you need a quick, offline quality audit of numeric source-to-transformed value pairs alongside category frequency counts, without requiring external data lookups or professional assessments. It is ideal for ETL validation, data transformation QA, and categorical breakdowns where all data is supplied inline and results are needed fast. It covers both quality and frequency in a single $0.01 call for up to 200 rows.

## Known failure modes

- Empty or malformed rows array returns a validation error
- Rows exceeding 200 items are rejected (maxItems limit)
- Missing required fields (row_id, dataset_group, date, source_value, transformed_value) cause schema validation failure
- Numeric values outside ±1,000,000,000,000 are rejected
- Malformed date strings not matching YYYY-MM-DD pattern fail validation
- Payment failure (insufficient USDC balance) prevents execution

## How this service works

Numeric precision comparisons — Record quality audit + Category frequencies: Record quality audit + Category frequencies 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: (1) a record quality audit identifying issues such as null values, mismatches, or precision anomalies across source and transformed numeric pairs, and (2) a category frequency summary showing how many records appear in each dataset_group. Both reports are computed locally 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
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/numeric-precision-comparisons-record-quality-audit-category-frequencies-d6ca4937/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)