# Company Headcount Observations — Record Quality Audit, String Normalisation & Exact Row Deduplication

> Company Headcount Observations — Record Quality Audit, String Normalisation & Exact Row Deduplication is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-15).

Audits, normalises, and deduplicates up to 200 company headcount observation records, returning three independent analytical reports using local engines — no external lookups or predictions.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-company-12-191?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-15
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/company-headcount-observations-record-quality-audit-string-8b70ed10
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_IE6iTWq-Ia_W3XdOAMrOZ

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-8b70ed10 -d '<json body>'
```

Example prompt: Can you run a quality audit, string normalisation, and exact deduplication check on these company headcount records I have — there are about 50 rows with company_group, date, headcount, and open_roles fields, and I want to get all three reports back at once?

## When to prefer this

Choose this endpoint when you need three combined data-quality operations — record auditing, string normalisation, and exact deduplication — on company headcount observation data in a single API call and want purely local, deterministic analysis without external lookups, predictions, or professional assessments. It is especially useful for data pipeline validation steps before loading headcount time series into a warehouse or analytics system.

## Known failure modes

- Submitting more than 200 rows returns an error as the batch limit is exceeded
- Missing required fields (row_id, company_group, date, headcount, open_roles) cause validation errors on the input schema
- Dates not matching YYYY-MM-DD pattern are rejected by schema validation
- row_id values exceeding 80 characters are rejected
- Numeric values for headcount or open_roles outside the allowed range cause schema rejection
- Payment of 0.01 USDC must be included; missing payment results in 402 response

## How this service works

Company headcount observations — Record quality audit + String normalisation + Exact row deduplication: Record quality audit + String normalisation + Exact row deduplication 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 reports covering: (1) a record quality audit flagging malformed, missing, or out-of-range values in headcount and open_roles fields; (2) a string normalisation report standardising company_group and other string fields; and (3) an exact row deduplication report identifying and removing fully duplicate rows — all generated locally 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
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/company-headcount-observations-record-quality-audit-string-8b70ed10/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)