# Company Headcount Observations — Numeric Interval Filter + Two-Measure Correlation

> Company Headcount Observations — Numeric Interval Filter + Two-Measure Correlation 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).

Filters company headcount observation rows by a numeric interval and computes a two-measure correlation (headcount vs open_roles) across up to 200 supplied rows in two independent analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-company-12-131?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-interval-filter-two-measure-1e07d793
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_CfcKgGq_7pJzFXgpayOKH

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-interval-filter-two-measure-1e07d793 -d '<json body>'
```

Example prompt: I have 150 company headcount snapshots with headcount and open_roles columns — can you filter to rows where headcount is between 50 and 500, and then run a correlation analysis between headcount and open_roles across all those records?

## When to prefer this

Choose this endpoint when you have a batch of company headcount observation records (up to 200 rows) and need both a numeric range filter on headcount or open_roles AND a correlation analysis between those two measures in a single $0.01 call. It is ideal for offline/supplied-data analytics where no live data fetch or prediction is needed, and when you want two packaged statistical outputs (interval filter + correlation) without building your own analytical pipeline.

## Known failure modes

- Empty or malformed rows array returns an error or empty report
- Date fields not matching YYYY-MM-DD pattern cause validation failure
- Rows exceeding 200-item limit are rejected
- Minimum greater than maximum produces an empty filtered set or error
- Null values in headcount or open_roles may reduce correlation sample size
- Missing required row fields (row_id, company_group, date) cause schema validation errors

## How this service works

Company headcount observations — Numeric interval filter + Two-measure correlation: Numeric interval filter + Two-measure correlation 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 independent analytical reports: (1) the rows from the supplied dataset that fall within the specified numeric interval for the chosen field, and (2) a correlation analysis between the headcount and open_roles measures across those records. Results 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"
  },
  "maximum": {
   "type": "number",
   "default": 100,
   "maximum": 1000000000000,
   "minimum": -1000000000000
  },
  "minimum": {
   "type": "number",
   "default": 0,
   "maximum": 1000000000000,
   "minimum": -1000000000000
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/company-headcount-observations-numeric-interval-filter-two-measure-1e07d793/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)