# Account Research Coverage Analyzer — Record Quality Audit, String Normalisation & Two-Measure Correlation

> Account Research Coverage Analyzer — Record Quality Audit, String Normalisation & Two-Measure Correlation is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-19).

Runs three offline analytical reports (record quality audit, string normalisation, and two-measure correlation) on supplied account research coverage data (researched_accounts vs target_accounts) for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-company-08-204?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-19
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/account-research-coverage-analyzer-record-quality-audit-string-3c1f608b
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_215bWDuDVIGPhvNgRQ5gC

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 account-research-coverage-analyzer-record-quality-audit-string-3c1f608b -d '<json body>'
```

Example prompt: Can you audit the data quality, normalise the company group strings, and run a correlation between researched_accounts and target_accounts for my coverage records? I have rows like: row-1, group-a, 2026-10-01, researched=10, target=1; row-2, group-b, 2026-10-02, researched=20, target=2.

## When to prefer this

Choose this endpoint when you need three bundled offline analytical reports — quality audit, string normalisation, and correlation — on account research coverage data (researched vs target accounts) for up to 200 rows, all in a single low-cost call. It is ideal when you already have the data locally and need no live enrichment, external lookups, or predictions — just structured analytical output on the supplied records.

## Known failure modes

- Fewer than 1 row supplied — validation error
- More than 200 rows supplied — rejected with maxItems error
- Invalid date format (not YYYY-MM-DD) — schema validation failure
- Numeric values outside ±1,000,000,000,000 range — rejected
- Missing required fields (row_id, company_group, date, researched_accounts, target_accounts) — schema error
- All researched_accounts or target_accounts values are null — correlation report may be empty or undefined

## How this service works

Account research coverage — Record quality audit + String normalisation + Two-measure correlation: Record quality audit + String normalisation + Two-measure correlation for supplied account research coverage records (researched_accounts, target_accounts). 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 for the supplied rows: (1) a record quality audit highlighting missing values, out-of-range numbers, or malformed dates; (2) a string normalisation report cleaning and standardising the company_group field; and (3) a two-measure correlation report quantifying the statistical relationship between researched_accounts and target_accounts. All analysis is performed locally on the supplied data with no external lookups.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/account-research-coverage-analyzer-record-quality-audit-string-3c1f608b/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)