# Account Research Coverage — String Normalisation + Exact Row Deduplication

> Account Research Coverage — String Normalisation + Exact Row Deduplication 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).

Normalises strings and deduplicates exact rows in account research coverage data (researched_accounts, target_accounts) across up to 200 rows, producing 2 analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-company-08-020?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-string-normalisation-exact-row-deduplication-63eed3cb
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_iWaSnmwyKBaeZ8q0PBhwq

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-string-normalisation-exact-row-deduplication-63eed3cb -d '<json body>'
```

Example prompt: Can you clean up my account research coverage data — normalise the company group strings and remove any exact duplicate rows? I have up to 50 rows with fields like row_id, company_group, date, researched_accounts, and target_accounts that need cleaning.

## When to prefer this

Choose this endpoint when you need lightweight, local string normalisation and exact-row deduplication on account research coverage data (researched_accounts and target_accounts) without requiring external lookups, predictions, or professional assessments. Ideal for data hygiene tasks on CRM or sales operations datasets of up to 200 rows at low cost ($0.01 USDC for 2 reports). Not suitable if you need fuzzy deduplication, enrichment, live data lookup, or processing more than 200 rows per call.

## Known failure modes

- Exceeding 200 rows causes rejection — keep input to maxItems limit
- Missing required fields (row_id, company_group, date, researched_accounts, target_accounts) will cause validation errors
- Malformed date strings not matching YYYY-MM-DD pattern will be rejected
- Numeric values outside the allowed range (-1,000,000,000,000 to 1,000,000,000,000) will fail schema validation
- Empty rows array will be rejected due to minItems:1 constraint

## How this service works

Account research coverage — String normalisation + Exact row deduplication: String normalisation + Exact row deduplication for supplied account research coverage records (researched_accounts, target_accounts). Up to 200 rows; 2 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 2 supplied-data reports for up to 200 rows.

## Output

Two analytical reports per call: one covering string normalisation results (standardised company group names, corrected formatting) and one covering exact row deduplication results (identified and removed duplicate rows), applied to the supplied account research coverage records (up to 200 rows). No external lookups or predictions are made; all analysis is performed locally on the supplied data.

## 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-string-normalisation-exact-row-deduplication-63eed3cb/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)