# Asset Coverage Data Quality Analyzer — Record Audit, String Normalisation & Correlation

> Asset Coverage Data Quality Analyzer — Record Audit, String Normalisation & Correlation is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-23).

Runs three local analytical reports on supplied asset coverage data: record quality audit, string normalisation, and two-measure correlation between known_assets and monitored_assets for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-security-10-204?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-23
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/asset-coverage-data-quality-analyzer-record-audit-string-a1e74dde
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_jZTYKHqIODwbDVEkyfnDZ

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 asset-coverage-data-quality-analyzer-record-audit-string-a1e74dde -d '<json body>'
```

Example prompt: Can you run a record quality audit, string normalisation, and correlation analysis on my asset coverage dataset? I have rows with control_group, date, known_assets, and monitored_assets fields — here are up to 200 rows of data I want analysed.

## When to prefer this

Choose this endpoint when you need three combined analytical operations on asset coverage data in a single call at low cost — specifically record quality auditing, string normalisation, and correlation between two numeric measures. Ideal for pre-analysis data cleaning and validation of asset tracking datasets up to 200 rows. Prefer this over separate quality tools when your data involves the specific known_assets/monitored_assets schema and you want bundled, offline local analysis without external lookups or live data enrichment.

## Known failure modes

- Input exceeds 200 rows — request will be rejected or truncated
- Missing required fields (row_id, control_group, date, known_assets, monitored_assets) cause validation errors
- Date strings not matching YYYY-MM-DD pattern are rejected
- Numeric values outside ±1,000,000,000,000 range are rejected
- Empty rows array returns an error
- Payment failure or insufficient USDC balance blocks processing

## How this service works

Asset coverage — Record quality audit + String normalisation + Two-measure correlation: Record quality audit + String normalisation + Two-measure correlation for supplied asset coverage records (known_assets, monitored_assets). Up to 200 rows; 3 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 3 supplied-data reports for up to 200 rows.

## Output

Returns three independent analytical reports: (1) a record quality audit identifying missing, malformed, or inconsistent values across the supplied rows; (2) a string normalisation report showing standardised versions of text fields like control_group; (3) a two-measure correlation report quantifying the statistical relationship between known_assets and monitored_assets values.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/asset-coverage-data-quality-analyzer-record-audit-string-a1e74dde/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)