# Company Headcount Observations — Record Quality Audit, String Normalisation & Date-by-Category Pivot

> Company Headcount Observations — Record Quality Audit, String Normalisation & 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).

Runs three local analytical reports on supplied company headcount data rows: a record quality audit, string normalisation, and a date-by-category pivot — no external lookups.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-company-12-206?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-record-quality-audit-string-7d8c4534
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_4SiraUnkWl5QqoP95Y5yp

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-record-quality-audit-string-7d8c4534 -d '<json body>'
```

Example prompt: Can you run a record quality audit, string normalisation, and date-by-category pivot on my company headcount data — I have rows with row_id, company_group, date, headcount, and open_roles fields, up to 200 rows, and I want to analyse the headcount field?

## When to prefer this

Choose this endpoint when you have up to 200 rows of company headcount observations and need a bundled set of three analytical reports — quality audit, string normalisation, and date pivot — in a single low-cost call ($0.01 USDC). It is purely local and analytical with no external lookups, making it safe for sensitive internal workforce data. Prefer it over general-purpose data tools when you specifically need the combination of quality auditing, string cleaning, and date-category pivoting on headcount or open_roles metrics in one pass.

## Known failure modes

- Fewer than 1 row supplied — request rejected
- More than 200 rows supplied — request rejected
- Invalid date format (not YYYY-MM-DD) — row-level validation error
- Missing required fields (row_id, company_group, date, headcount, open_roles) — schema validation failure
- field enum value not 'headcount' or 'open_roles' — rejected
- Numeric values outside allowed range — flagged or rejected

## How this service works

Company headcount observations — Record quality audit + String normalisation + Date by category pivot: Record quality audit + String normalisation + Date by category pivot for supplied company headcount observations records (headcount, open_roles). Up to 200 rows; 3 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 3 supplied-data reports for up to 200 rows.

## Output

Three independent analytical reports based solely on the supplied rows: (1) a record quality audit flagging malformed, missing, or out-of-range values; (2) string normalisation suggestions for the company_group field; and (3) a date-by-category pivot table for the selected numeric field (headcount or open_roles). No external data is fetched.

## 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-record-quality-audit-string-7d8c4534/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)