# Company Headcount Observations — Record Quality Audit + String Normalisation + IQR Outlier Flags

> Company Headcount Observations — Record Quality Audit + String Normalisation + IQR Outlier Flags 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 record quality, normalises strings, and flags IQR-based outliers across up to 200 company headcount observation rows, returning 3 independent analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-company-12-203?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-1afc6436
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_e-v_Yskv3N64gXwhxVnpa

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-1afc6436 -d '<json body>'
```

Example prompt: Can you audit the quality of these company headcount records, normalise the company_group strings, and flag any IQR outliers in the headcount field? I have up to 50 rows with row_id, company_group, date, headcount, and open_roles — I need all 3 reports back.

## When to prefer this

Choose this endpoint when you have up to 200 company headcount observation rows and need three simultaneous analytical passes — quality auditing, string normalisation, and IQR outlier detection — in a single low-cost call. It is ideal for pre-ingestion data validation, HR data pipeline hygiene, or workforce reporting prep where all three checks are needed together rather than separately. Prefer sibling endpoints if you only need one or two of these operations, or if you need deduplication, distribution analysis, or base-100 indexing instead.

## Known failure modes

- Rows exceeding 200 items will be rejected — ensure input array has at most 200 entries
- Missing required fields (row_id, company_group, date, headcount, open_roles) per row will cause validation errors
- Dates not matching YYYY-MM-DD pattern will be flagged or rejected
- Numeric values outside allowed range (±1 trillion) will fail schema validation
- Empty rows array (minItems: 1 not met) will return an error
- Invalid field enum value (must be 'headcount' or 'open_roles') will cause a bad request

## How this service works

Company headcount observations — Record quality audit + String normalisation + IQR outlier flags: Record quality audit + String normalisation + IQR outlier flags 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 covering: (1) a record quality audit identifying missing, malformed, or inconsistent fields; (2) string normalisation results for company_group and other text fields; and (3) IQR-based outlier flags indicating which rows contain anomalous headcount or open_roles values. All analysis is performed on 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"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/company-headcount-observations-record-quality-audit-string-1afc6436/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)