# Company Headcount Observations — Category Frequencies & Date-by-Category Pivot

> Company Headcount Observations — 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 2026-10-19).

Runs two analytical reports on supplied company headcount data: category frequency counts and a date-by-category pivot table, for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-company-12-110?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/company-headcount-observations-category-frequencies-date-by-category-90675488
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_Kf1Nm9gacs3Ud-TGCAOGq

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 company-headcount-observations-category-frequencies-date-by-category-90675488 -d '<json body>'
```

Example prompt: I have headcount observation records for several company groups — can you run category frequency counts and a date-by-category pivot on them? The field I care about is headcount, and here are my rows: group-a had 10 employees on 2024-01-01 with 1 open role, group-b had 20 employees on 2024-01-01 with 3 open roles, group-a had 12 on 2024-02-01 with 2 open roles.

## When to prefer this

Choose this endpoint when you have up to 200 rows of company headcount observations (with company_group, date, headcount, and open_roles fields) and need both a category frequency summary and a date-by-category pivot in a single low-cost call. Ideal for HR analysts, workforce planners, or agent pipelines that need structured summaries of headcount data without building custom analytics. Not suitable for live data lookup, prediction, or datasets exceeding 200 rows.

## Known failure modes

- Rows array is empty or missing — returns validation error
- More than 200 rows supplied — request rejected, maxItems exceeded
- Invalid date format (not YYYY-MM-DD) — schema pattern validation fails
- Missing required fields (row_id, company_group, date, headcount, open_roles) — request rejected
- Invalid field selector (not 'headcount' or 'open_roles') — enum validation fails
- Null numeric values may be excluded or treated as missing in pivot output

## How this service works

Company headcount observations — Category frequencies + Date by category pivot: Category frequencies + Date by category pivot for supplied company headcount observations records (headcount, open_roles). 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: (1) a category frequency table showing how often each company_group value appears in the supplied rows, and (2) a date-by-category pivot table showing the selected field (headcount or open_roles) values broken down by date and company_group. Both reports are computed locally on the supplied data with no external lookups.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "rows": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "row_id",
     "company_group",
     "date",
     "headcount",
     "open_roles"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "maxLength": 10
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "headcount": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "open_roles": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "company_group": {
      "type": "string",
      "default": "",
      "maxLength": 80
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "headcount": 10,
     "open_roles": 1,
     "company_group": "group-a"
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "headcount": 20,
     "open_roles": 2,
     "company_group": "group-b"
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "headcount": 15,
     "open_roles": 3,
     "company_group": "group-a"
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "headcount": 30,
     "open_roles": 4,
     "company_group": "group-b"
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "headcount",
    "open_roles"
   ],
   "type": "string",
   "default": "headcount"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/company-headcount-observations-category-frequencies-date-by-category-90675488/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)