# Account Research Coverage — Numeric Row Ordering + IQR Outlier Flags

> Account Research Coverage — Numeric Row Ordering + IQR Outlier Flags 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).

Ranks and IQR-flags up to 200 account research coverage records (researched_accounts or target_accounts) across two independent analytical reports using local statistical engines.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-company-08-119?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-numeric-row-ordering-iqr-outlier-flags-df1f8c78
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_bpwqFipf2ibOX0_wuT5f5

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-numeric-row-ordering-iqr-outlier-flags-df1f8c78 -d '<json body>'
```

Example prompt: I have 4 rows of account research coverage data — row-1 through row-4 for group-a and group-b dated 2026-10-01 to 2026-10-04, with researched_accounts values of 10, 20, 15, and 30 — can you rank these rows by researched_accounts and flag any IQR outliers?

## When to prefer this

Choose this endpoint when you have up to 200 tabular account research coverage records and need both numeric row ordering and IQR-based outlier detection in a single call. It is ideal for sales operations or CRM analytics workflows where you supply your own data and need fast, local statistical analysis without any external lookups, predictions, or live data enrichment. At $0.01 USDC for two reports, it is cost-effective for lightweight statistical QA on coverage datasets.

## Known failure modes

- Input array has fewer than 1 or more than 200 rows — validation error
- Missing required fields (row_id, company_group, date, researched_accounts, target_accounts) on any row — schema rejection
- Invalid date format (not YYYY-MM-DD) — pattern validation failure
- Field selector not one of 'researched_accounts' or 'target_accounts' — enum validation error
- All values null for the selected field — IQR computation undefined
- Payment not included or insufficient (requires 0.01 USDC via x402) — 402 response

## How this service works

Account research coverage — Numeric row ordering + IQR outlier flags: Numeric row ordering + IQR outlier flags 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 independent analytical reports covering: (1) numeric row ordering of the specified field (researched_accounts or target_accounts) across up to 200 input rows, and (2) IQR-based outlier flags identifying statistically extreme values. Reports are generated locally with no external lookups or live 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
  },
  "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-numeric-row-ordering-iqr-outlier-flags-df1f8c78/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)