# Company Filing Inventories — Record Quality Audit + String Normalisation + Numeric Distribution

> Company Filing Inventories — Record Quality Audit + String Normalisation + Numeric Distribution is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-20).

Runs three local analytical reports (record quality audit, string normalisation, and numeric distribution) on up to 200 rows of company filing inventory data (available_filings, expected_filings).

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-company-17-193?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-20
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/company-filing-inventories-record-quality-audit-string-normalisation-59c1f21a
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_q7hUQM0jcy4xk8C3fO6ct

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-filing-inventories-record-quality-audit-string-normalisation-59c1f21a -d '<json body>'
```

Example prompt: Can you run a record quality audit, string normalisation, and numeric distribution analysis on my company filing inventory data? I have rows with company_group, date, available_filings, and expected_filings — here are up to 200 rows, and I want to analyse the available_filings field.

## When to prefer this

Choose this endpoint when you need three simultaneous local analytical reports — quality audit, string normalisation, and numeric distribution — on company filing inventory data (available_filings / expected_filings) in a single low-cost call. It is ideal for pre-load data validation, quick EDA on filing counts, and normalisation of company group strings, all without any external data lookups or live predictions. Best suited for batches of 1–200 rows at $0.01 USDC per call.

## Known failure modes

- Exceeding 200 rows causes rejection — keep batch at or below the maximum
- Missing required fields (row_id, date, company_group, available_filings, expected_filings) will cause validation errors
- Invalid date format (not YYYY-MM-DD) will fail pattern validation
- Numeric values outside ±1,000,000,000,000 range will be rejected
- Empty rows array is not accepted (minItems: 1)

## How this service works

Company filing inventories — Record quality audit + String normalisation + Numeric distribution: Record quality audit + String normalisation + Numeric distribution for supplied company filing inventories records (available_filings, expected_filings). 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

Returns three independent analytical reports for the submitted rows: (1) a record quality audit flagging completeness and validity issues, (2) a string normalisation report for company_group and date fields, and (3) a numeric distribution summary (e.g. min, max, mean, percentiles) for the selected numeric field (available_filings or expected_filings).

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "rows": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "row_id",
     "company_group",
     "date",
     "available_filings",
     "expected_filings"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "maxLength": 10
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "company_group": {
      "type": "string",
      "default": "",
      "maxLength": 80
     },
     "expected_filings": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "available_filings": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "company_group": "group-a",
     "expected_filings": 1,
     "available_filings": 10
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "company_group": "group-b",
     "expected_filings": 2,
     "available_filings": 20
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "company_group": "group-a",
     "expected_filings": 3,
     "available_filings": 15
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "company_group": "group-b",
     "expected_filings": 4,
     "available_filings": 30
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "available_filings",
    "expected_filings"
   ],
   "type": "string",
   "default": "available_filings"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/company-filing-inventories-record-quality-audit-string-normalisation-59c1f21a/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)