# Account Research Coverage — Record Quality Audit + String Normalisation + Numeric Distribution

> Account Research Coverage — Record Quality Audit + String Normalisation + Numeric Distribution 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).

Audits record quality, normalises strings, and computes numeric distributions for up to 200 account research coverage rows across researched_accounts and target_accounts fields.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-company-08-193?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-record-quality-audit-string-normalisation-39c81a9f
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_V9Idio7D2j47enzZK-VV2

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-record-quality-audit-string-normalisation-39c81a9f -d '<json body>'
```

Example prompt: Can you run a record quality audit, string normalisation, and numeric distribution on my account research coverage data — here are 4 rows with row_id, company_group, date, researched_accounts, and target_accounts — and focus the distribution on the researched_accounts field?

## When to prefer this

Choose this endpoint when you need three bundled analytical reports — quality audit, string normalisation, and numeric distribution — on account research coverage data (researched_accounts, target_accounts) in a single low-cost call. Ideal for pre-processing CRM or sales intelligence exports before downstream analysis, when you have up to 200 rows and want to avoid separate API calls for each report type. Do not use if you need live account lookups, predictive scoring, or external data enrichment.

## Known failure modes

- Fewer than 1 row supplied — request rejected
- More than 200 rows supplied — exceeds batch limit
- Invalid date format (not YYYY-MM-DD) — schema validation error
- Missing required fields (row_id, company_group, date, researched_accounts, target_accounts) — validation failure
- Numeric values outside ±1,000,000,000,000 range — schema rejection
- Invalid field enum value (not researched_accounts or target_accounts) — error

## How this service works

Account research coverage — Record quality audit + String normalisation + Numeric distribution: Record quality audit + String normalisation + Numeric distribution 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 flagging missing, malformed, or out-of-range values; (2) a string normalisation report standardising company_group and other string fields; and (3) a numeric distribution report summarising the selected numeric field (researched_accounts or target_accounts) across the dataset.

## 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
  },
  "field": {
   "enum": [
    "researched_accounts",
    "target_accounts"
   ],
   "type": "string",
   "default": "researched_accounts"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/account-research-coverage-record-quality-audit-string-normalisation-39c81a9f/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)