# Account Research Coverage — Base-100 Series + Explicit Missing-Value Fill

> Account Research Coverage — Base-100 Series + Explicit Missing-Value Fill is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-15).

Normalizes account research coverage time-series data to a base-100 index and fills missing values using zero, mean, or median strategies, producing two analytical reports from supplied data.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-company-08-169?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-15
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/account-research-coverage-base-100-series-explicit-missing-value-fill-232ae260
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_FE6sor6rZV_RPJGtylnkX

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-base-100-series-explicit-missing-value-fill-232ae260 -d '<json body>'
```

Example prompt: I have 4 rows of account research data for two groups — group-a and group-b — with dates from 2026-10-01 to 2026-10-04, researched_accounts values of 10, 20, 15, 30 and target_accounts of 1, 2, 3, 4. Can you normalize the researched_accounts field to a base-100 index starting at row 0, and fill any missing values using median?

## When to prefer this

Choose this endpoint when you have up to 200 rows of account research coverage data (researched_accounts and/or target_accounts) that need both base-100 normalization and missing-value imputation in a single call. It is ideal for sales ops or CRM analytics workflows where you want to compare time-series data across company groups on a common index without any live lookups or external enrichment. Prefer this over generic stats tools when you need both reports delivered together cheaply at $0.01 USDC per call.

## Known failure modes

- Fewer than 1 or more than 200 rows submitted — validation error
- Date field not matching YYYY-MM-DD pattern — schema validation failure
- base_index value exceeds the number of submitted rows — index out of bounds error
- All values in the selected field are null — mean/median fill may produce undefined results
- Non-numeric values passed for researched_accounts or target_accounts — type validation failure

## How this service works

Account research coverage — Base-100 series + Explicit missing-value fill: Base-100 series + Explicit missing-value fill 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: (1) a base-100 indexed time series for the selected field (researched_accounts or target_accounts) anchored at the specified base row, and (2) an explicit missing-value fill report using the chosen strategy (zero, mean, or median). Both reports are computed locally from the supplied rows with no external data sources.

## 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"
  },
  "method": {
   "enum": [
    "zero",
    "mean",
    "median"
   ],
   "type": "string",
   "default": "median"
  },
  "base_index": {
   "type": "integer",
   "default": 0,
   "maximum": 199,
   "minimum": 0
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/account-research-coverage-base-100-series-explicit-missing-value-fill-232ae260/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)