# Company Headcount Observations — Numeric Row Ordering + Secondary-Measure Weighted Mean

> Company Headcount Observations — Numeric Row Ordering + Secondary-Measure Weighted Mean is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-11-02).

Computes numeric row ordering and a secondary-measure weighted mean for up to 200 company headcount observation records (headcount, open_roles) in two bundled analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-company-12-121?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-11-02
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/company-headcount-observations-numeric-row-ordering-secondary-measure-52622409
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_njR_BTF3k-25VRMa922-_

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-numeric-row-ordering-secondary-measure-52622409 -d '<json body>'
```

Example prompt: I have a dataset of company headcount observations with dates, company groups, headcount, and open_roles — can you rank these rows numerically and compute a weighted mean using headcount as the primary field? Here are the records: row-1 (group-a, 2024-01-01, headcount=50, open_roles=3), row-2 (group-b, 2024-01-01, headcount=120, open_roles=10), row-3 (group-a, 2024-01-02, headcount=55, open_roles=4).

## When to prefer this

Choose this endpoint when you have up to 200 company headcount observation records and need both a numeric row ordering and a secondary-measure weighted mean in a single low-cost call ($0.01 USDC for two reports). It is best suited for offline/batch analytical tasks on supplied data — not for live HR system queries, forecasting, or real-time lookups. Ideal for workforce analysts who want bundled statistical summaries without building custom aggregation logic.

## Known failure modes

- More than 200 rows submitted — API rejects input exceeding maxItems limit
- Missing required fields (row_id, company_group, date, headcount, or open_roles) cause validation errors
- Invalid date format (not YYYY-MM-DD) results in schema validation failure
- Null values in headcount or open_roles may produce undefined weighted mean if all weights are null
- Invalid field enum value (not 'headcount' or 'open_roles') causes rejection

## How this service works

Company headcount observations — Numeric row ordering + Secondary-measure weighted mean: Numeric row ordering + Secondary-measure weighted mean 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 for the supplied dataset: (1) numeric row ordering — each row ranked or ordered by its numeric value; and (2) a secondary-measure weighted mean — a weighted average of either headcount or open_roles, where the secondary measure provides the weights. Both reports are computed locally 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-numeric-row-ordering-secondary-measure-52622409/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)