# Company Headcount Observations — Numeric Row Ordering + Daily Sum Series

> Company Headcount Observations — Numeric Row Ordering + Daily Sum Series 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 numeric row ordering and a daily sum time series for company headcount or open-roles data across up to 200 rows, returning two analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-company-12-114?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-daily-sum-series-8f70d91f
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_tVuhUo8zsU-WdTuNPH7qa

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-daily-sum-series-8f70d91f -d '<json body>'
```

Example prompt: Rank these company headcount rows numerically and give me a daily sum series for the headcount field — I have 4 records: row-1 on 2026-10-01 for group-a with headcount 10 and 1 open role, row-2 on 2026-10-02 for group-b with headcount 20 and 2 open roles, row-3 on 2026-10-03 for group-a with headcount 15 and 3 open roles, row-4 on 2026-10-04 for group-b with headcount 30 and 4 open roles.

## When to prefer this

Choose this endpoint when you need two specific analytical outputs — numeric row ordering and a daily sum time series — for company headcount or open-roles data in a single low-cost call. It is ideal for HR analytics pipelines, workforce tracking dashboards, or data validation workflows where you already have the observation data locally and need fast, deterministic computation without live data lookups or predictions.

## Known failure modes

- Missing required fields (row_id, company_group, date, headcount, open_roles) cause validation errors
- Date strings not matching YYYY-MM-DD pattern are rejected
- Submitting more than 200 rows exceeds the row limit and will be rejected
- Empty rows array (minItems: 1 violated) returns an error
- Invalid field enum value (anything other than 'headcount' or 'open_roles') causes a schema error
- Null numeric values for both headcount and open_roles may produce incomplete aggregations

## How this service works

Company headcount observations — Numeric row ordering + Daily sum series: Numeric row ordering + Daily sum series 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 reports: (1) a numeric row ordering of the supplied headcount records, and (2) a daily sum time series for the selected field (headcount or open_roles), aggregated across all company groups per date. Both reports are computed locally 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-daily-sum-series-8f70d91f/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)