# Company Headcount Observations — Secondary-Measure Weighted Mean + Date by Category Pivot

> Company Headcount Observations — Secondary-Measure Weighted Mean + 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).

Computes a secondary-measure weighted mean and a date-by-category pivot table for supplied company headcount and open-roles data (up to 200 rows, 2 reports per call).

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-company-12-185?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-secondary-measure-weighted-mean-date-cc137da9
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_kyd_vSGB5c8eE3HgYCPgr

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-secondary-measure-weighted-mean-date-cc137da9 -d '<json body>'
```

Example prompt: I have headcount observations for two company groups across several dates — can you compute the weighted mean of open_roles weighted by headcount, and also give me a pivot table of headcount by date and company group? Here are the rows: row-1, 2024-01-01, group-a, headcount 100, open_roles 5; row-2, 2024-01-01, group-b, headcount 200, open_roles 12; row-3, 2024-01-02, group-a, headcount 110, open_roles 7; row-4, 2024-01-02, group-b, headcount 190, open_roles 9.

## When to prefer this

Choose this endpoint when you have pre-collected company headcount or open-roles tabular data and need both a weighted mean summary statistic and a date-by-category pivot in a single low-cost call. It is ideal for offline batch analytics on workforce snapshots without needing live data lookup or external enrichment. At $0.01 USDC for two reports on up to 200 rows, it is cost-effective for periodic reporting pipelines.

## Known failure modes

- Missing required fields (row_id, company_group, date, headcount, open_roles) causes validation error
- More than 200 rows supplied exceeds limit and is rejected
- Invalid date format (not YYYY-MM-DD) causes schema rejection
- Null values in both headcount and open_roles may affect weighted mean computation
- Invalid field enum value (not 'headcount' or 'open_roles') causes error
- Empty rows array rejected (minItems: 1)

## How this service works

Company headcount observations — Secondary-measure weighted mean + Date by category pivot: Secondary-measure weighted mean + 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

Returns two analytical reports: (1) a secondary-measure weighted mean computed over the supplied rows using the selected field (headcount or open_roles), and (2) a pivot table cross-tabulating values by date and company_group category. Both reports are derived entirely from 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-secondary-measure-weighted-mean-date-cc137da9/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)