# Account Research Coverage — Record Quality Audit + String Normalisation + Duplicate Key Report

> Account Research Coverage — Record Quality Audit + String Normalisation + Duplicate Key Report 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, normalises, and deduplicates up to 200 rows of account research coverage data (researched_accounts, target_accounts) across three independent local analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-company-08-192?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-c3caf496
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_VxZZyYfBuVmBZqlcYKzp8

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-c3caf496 -d '<json body>'
```

Example prompt: Can you run a record quality audit, string normalisation, and duplicate key check on my account research coverage data? I have rows with fields like row_id, company_group, date, researched_accounts, and target_accounts — here are my 50 rows spanning October 2026 across groups like 'group-a' and 'group-b'.

## When to prefer this

Choose this endpoint when you need to simultaneously audit data quality, normalise string fields, and detect duplicate keys in account research coverage data in a single $0.01 call. It is ideal for pre-ingestion validation of CRM or sales research datasets with up to 200 rows where no live lookups, predictions, or external enrichment are needed — just fast, local analytical reports on supplied data.

## Known failure modes

- Input array exceeds 200 rows — request will be rejected or truncated
- Missing required fields (row_id, company_group, date, researched_accounts, target_accounts) cause row-level validation errors
- Date strings not matching YYYY-MM-DD pattern are flagged or rejected
- Numeric values for researched_accounts or target_accounts outside allowed range cause validation errors
- Empty rows array (minItems:1 not met) results in an error response
- Payment of 0.01 USDC not confirmed causes request rejection

## How this service works

Account research coverage — Record quality audit + String normalisation + Duplicate key report: Record quality audit + String normalisation + Duplicate key report 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

Three independent reports: (1) a record quality audit flagging missing, malformed, or out-of-range values; (2) a string normalisation report identifying and standardising inconsistencies in text fields like company_group; (3) a duplicate key report identifying rows sharing identical key combinations. All analysis is performed locally 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-record-quality-audit-string-normalisation-c3caf496/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)