# Account Research Coverage Analyzer — Record Quality Audit, String Normalisation & Adjacent Row Changes

> Account Research Coverage Analyzer — Record Quality Audit, String Normalisation & Adjacent Row Changes is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-16).

Runs three local analytical reports (record quality audit, string normalisation, and adjacent row changes) on up to 200 rows of account research coverage data containing researched_accounts and target_accounts fields.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-company-08-200?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-16
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/account-research-coverage-analyzer-record-quality-audit-string-37d1428d
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_8tLox5hEeQwtcODHTJgYx

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-37d1428d -d '<json body>'
```

Example prompt: Can you run the three account research coverage reports — record quality audit, string normalisation, and adjacent row changes — on my dataset of researched_accounts? Here are up to 200 rows with row_id, company_group, date, researched_accounts, and target_accounts values.

## When to prefer this

Choose this endpoint when you need all three analytical perspectives — data quality, string normalisation, and sequential change detection — on account research coverage records in a single low-cost call. It is ideal for pre-import validation, periodic data hygiene checks, or diagnosing issues in sales or CRM datasets. It does not perform live lookups, predictions, or external enrichment, so prefer it when you want purely local, deterministic analysis of supplied data rather than external intelligence.

## Known failure modes

- Rows array empty or missing — returns validation error
- More than 200 rows supplied — exceeds maxItems limit
- Invalid date format (not YYYY-MM-DD) — schema pattern mismatch
- row_id missing or blank — required field violation
- Numeric values outside ±1,000,000,000,000 range — schema validation failure
- Invalid field enum value (not researched_accounts or target_accounts) — rejected
- Payment of 0.01 USDC not completed — 402 Payment Required response

## How this service works

Account research coverage — Record quality audit + String normalisation + Adjacent row changes: Record quality audit + String normalisation + Adjacent row changes 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 analytical reports delivered together: (1) a record quality audit flagging missing, null, or out-of-range values in the supplied rows; (2) a string normalisation report identifying formatting inconsistencies in text fields like company_group; and (3) an adjacent row changes report showing period-over-period differences in the selected numeric field (researched_accounts or target_accounts). 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
  },
  "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-analyzer-record-quality-audit-string-37d1428d/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)