# Company Headcount Observations — Record Quality Audit, String Normalisation & Numeric Row Ordering

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

Audits data quality, normalises strings, and orders rows numerically for up to 200 company headcount observation records (headcount and open_roles fields) across 3 independent analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-company-12-196?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-0093db10
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_EN_Q-0k1Fs60uYBzhf8wX

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-0093db10 -d '<json body>'
```

Example prompt: Can you run a record quality audit, string normalisation, and numeric ordering on these company headcount observations I have for group-a and group-b — I've got headcount and open_roles figures for each date and want all three reports back at once?

## When to prefer this

Choose this endpoint when you need three bundled data-quality operations (audit, string normalisation, numeric ordering) on company headcount observation records in a single cost-effective call ($0.01 USDC for all three reports on up to 200 rows). Prefer this over general-purpose data tools when your data specifically contains headcount and open_roles fields grouped by company and date, and you need no live lookups or external enrichment — only local analytical processing of supplied rows.

## Known failure modes

- Exceeding 200 rows returns an error or processes only up to the limit
- Rows missing required fields (row_id, company_group, date, headcount, open_roles) fail validation
- Date strings not matching YYYY-MM-DD pattern are rejected
- Null numeric values may affect ordering report output
- Field selector not matching 'headcount' or 'open_roles' enum causes rejection

## How this service works

Company headcount observations — Record quality audit + String normalisation + Numeric row ordering: Record quality audit + String normalisation + Numeric row ordering 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: (1) a record quality audit flagging issues in the supplied headcount/open_roles rows, (2) a string normalisation report standardising fields like company_group, and (3) a numeric row ordering report sorting rows by the selected numeric field (headcount or open_roles). No external data is fetched; all analysis is performed on the supplied rows only.

## 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-0093db10/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)