# Liquidity Observations — Record Quality Audit + IQR Outlier Flags

> Liquidity Observations — Record Quality Audit + IQR Outlier Flags is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-28).

Performs a record quality audit and IQR-based outlier detection on up to 200 rows of liquidity observation data (base_quantity and quote_quantity fields), returning two independent analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-finance-10-014?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-28
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/liquidity-observations-record-quality-audit-iqr-outlier-flags-f03160bd
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_9ntQGZneJaQg7ubsppBrF

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 liquidity-observations-record-quality-audit-iqr-outlier-flags-f03160bd -d '<json body>'
```

Example prompt: Can you run a record quality audit and IQR outlier check on my liquidity observations? I have rows with base_quantity and quote_quantity across groups like 'group-a' and 'group-b' from 2026-10-01 through 2026-10-04 — flag any outliers in the base_quantity field.

## When to prefer this

Choose this endpoint when you need a combined record quality audit plus IQR outlier detection specifically for liquidity observation data with base_quantity and quote_quantity fields. It is best suited for financial data pipelines, pre-analysis data validation, or regular data quality checks on market liquidity records with up to 200 rows per call. Prefer this over general statistics endpoints when you specifically need both a quality audit and outlier flagging in a single call at low cost.

## Known failure modes

- Submitting more than 200 rows returns a validation error
- Missing required fields (row_id, instrument_group, date, base_quantity, quote_quantity) causes row rejection
- Invalid date format (not YYYY-MM-DD) triggers schema validation failure
- Quantities outside the ±1,000,000,000,000 range are rejected
- Empty rows array returns an error
- Payment failure (insufficient USDC) prevents report generation

## How this service works

Liquidity observations — Record quality audit + IQR outlier flags: Record quality audit + IQR outlier flags for supplied liquidity observations records (base_quantity, quote_quantity). 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 identifying missing values, format issues, and data integrity problems across the supplied rows; and (2) IQR-based outlier flags identifying which rows have base_quantity or quote_quantity values that fall outside the interquartile range threshold. Results are computed locally with no external lookups.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "rows": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "row_id",
     "instrument_group",
     "date",
     "base_quantity",
     "quote_quantity"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "maxLength": 10
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "base_quantity": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "quote_quantity": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "instrument_group": {
      "type": "string",
      "default": "",
      "maxLength": 80
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "base_quantity": 10,
     "quote_quantity": 1,
     "instrument_group": "group-a"
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "base_quantity": 20,
     "quote_quantity": 2,
     "instrument_group": "group-b"
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "base_quantity": 15,
     "quote_quantity": 3,
     "instrument_group": "group-a"
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "base_quantity": 30,
     "quote_quantity": 4,
     "instrument_group": "group-b"
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "base_quantity",
    "quote_quantity"
   ],
   "type": "string",
   "default": "base_quantity"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/liquidity-observations-record-quality-audit-iqr-outlier-flags-f03160bd/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)