# Numeric Precision Comparisons — Record Quality Audit + Trailing Mean Series

> Numeric Precision Comparisons — Record Quality Audit + Trailing Mean Series 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).

Performs two analytical reports on supplied numeric pairs (source_value, transformed_value): a record quality audit and a trailing mean series, for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-20-010?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-trailing-mean-series-5dbcc81a
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_DuE4TOX71aw677r7hbfCs

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-trailing-mean-series-5dbcc81a -d '<json body>'
```

Example prompt: Can you run a record quality audit and trailing mean series (window size 5) on my dataset — I'll provide up to 50 rows with source_value and transformed_value pairs, grouped by category, dated daily, and I want the analysis on the source_value field?

## When to prefer this

Choose this endpoint when you need both a record-level data quality audit and a rolling mean time series computed together on a batch of up to 200 numeric comparison rows — especially for validating ETL transformations or numeric precision pipelines without any external data lookups or live predictions. It is cost-effective at $0.01 USDC for both reports simultaneously.

## Known failure modes

- Fewer than 1 row or more than 200 rows supplied causes rejection
- Missing required fields (row_id, date, dataset_group, source_value, transformed_value) cause validation errors
- Invalid date format (not YYYY-MM-DD) causes schema rejection
- Window size outside 2–200 range is rejected
- Numeric values outside ±1,000,000,000,000 are rejected
- Payment of 0.01 USDC not included causes authorization failure

## How this service works

Numeric precision comparisons — Record quality audit + Trailing mean series: Record quality audit + Trailing mean series 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 record quality audit flagging issues at the row level for each source_value/transformed_value pair, and (2) a trailing mean series for the selected field (source_value or transformed_value) over the specified rolling window — both 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
  },
  "field": {
   "enum": [
    "source_value",
    "transformed_value"
   ],
   "type": "string",
   "default": "source_value"
  },
  "window": {
   "type": "integer",
   "default": 2,
   "maximum": 200,
   "minimum": 2
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/numeric-precision-comparisons-record-quality-audit-trailing-mean-series-5dbcc81a/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)