# Account Research Coverage — Category Frequencies + Date by Category Pivot

> Account Research Coverage — Category Frequencies + Date by Category Pivot is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-21).

Runs two local analytical reports on account research coverage data: category frequency counts and a date-by-category pivot table for researched_accounts or target_accounts.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-company-08-110?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-21
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/account-research-coverage-category-frequencies-date-by-category-pivot-bf25003a
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_8ynG16N5LcGTFZdSSN4F5

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-category-frequencies-date-by-category-pivot-bf25003a -d '<json body>'
```

Example prompt: I have up to 200 rows of account research coverage data with company_group, date, researched_accounts, and target_accounts — can you run both the category frequency breakdown and the date-by-category pivot on the researched_accounts field for me?

## When to prefer this

Choose this endpoint when you have up to 200 rows of account research coverage records and need both a category frequency breakdown and a date-by-category pivot in a single $0.01 call. It is ideal for quick offline analytical summaries without requiring an external BI tool, database, or live data connection. Prefer this over generic analytics APIs when your data is already structured with company_group, date, researched_accounts, and target_accounts fields.

## Known failure modes

- Rows array empty or missing — returns validation error
- More than 200 rows submitted — exceeds max row limit
- Invalid date format (not YYYY-MM-DD) — schema validation failure
- Invalid field value (not researched_accounts or target_accounts) — enum validation error
- Null values in required fields like row_id — schema rejection
- Payment not included or insufficient — x402 payment required error

## How this service works

Account research coverage — Category frequencies + Date by category pivot: Category frequencies + Date by category pivot 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

Returns two analytical reports: (1) category frequency counts showing how often each company_group appears in the dataset for the selected metric, and (2) a date-by-category pivot table cross-tabulating dates against company groups for the chosen field (researched_accounts or target_accounts). Both reports are computed locally on the supplied rows with no external data 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-category-frequencies-date-by-category-pivot-bf25003a/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)