# Company Headcount Observations — Numeric Row Ordering + IQR Outlier Flags

> Company Headcount Observations — Numeric Row Ordering + IQR Outlier Flags 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).

Analyzes up to 200 company headcount observation rows by computing numeric row ordering and IQR-based outlier flags for headcount or open_roles fields.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-company-12-119?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-numeric-row-ordering-iqr-outlier-flags-2c1fadd8
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_Q_Dq0i83f5l7r-CPfZxhx

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-iqr-outlier-flags-2c1fadd8 -d '<json body>'
```

Example prompt: I have a set of company headcount observations across different groups — can you rank them numerically and flag any IQR outliers in the headcount field? Here are up to 200 rows with row IDs, company groups, dates, headcount counts, and open roles.

## When to prefer this

Choose this endpoint when you have a batch of up to 200 company headcount or open-roles records and need both a numeric ranking and IQR-based outlier detection in a single call. It is ideal for HR analytics, workforce data auditing, or identifying anomalous headcount entries without requiring external data sources or predictions. Prefer this over general-purpose statistical tools when you need a lightweight, cost-effective ($0.01 USDC) packaged analysis of supplied workforce data.

## Known failure modes

- Input array exceeds 200 rows — request will be rejected or truncated
- Missing required fields (row_id, company_group, date, headcount, open_roles) cause row-level errors
- Invalid date format (must match YYYY-MM-DD pattern) causes parsing failures
- All-null values for the selected field may produce empty or degenerate IQR results
- Insufficient data variance may result in trivial outlier flags (all or none flagged)

## How this service works

Company headcount observations — Numeric row ordering + IQR outlier flags: Numeric row ordering + IQR outlier flags 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 up to 200 input rows: (1) a numeric ordering/ranking of rows by the selected field (headcount or open_roles), and (2) IQR-based outlier flags identifying which rows contain statistically anomalous values. Results are derived entirely from the supplied data using local analytical engines — no external lookups are performed.

## 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-iqr-outlier-flags-2c1fadd8/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)