# Company Filing Inventories — Record Quality Audit + String Normalisation

> Company Filing Inventories — Record Quality Audit + String Normalisation 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).

Audits data quality and normalises strings for up to 200 rows of company filing inventory records (available_filings, expected_filings), producing two independent analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-company-17-001?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-bc0a8945
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_goIaQBfFwoaBf9Q_GbEVo

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-bc0a8945 -d '<json body>'
```

Example prompt: Can you run a record quality audit and string normalisation on my company filing inventory data? I have about 50 rows with fields like row_id, company_group, date, available_filings, and expected_filings — I want to get two reports back covering data quality issues and normalised strings.

## When to prefer this

Choose this endpoint when you need simultaneous record quality auditing and string normalisation for company filing inventory data (available_filings, expected_filings) in a single low-cost call. It is ideal for pre-processing filing datasets before analysis or submission, catching null values, format errors, and inconsistent strings across up to 200 rows. Prefer it over generic data quality tools when your data specifically involves company filing counts and group identifiers. Not suitable for live data lookup, prediction, or professional compliance assessment.

## Known failure modes

- Exceeding 200 rows returns a validation error
- Rows missing required fields (row_id, company_group, date, available_filings, expected_filings) are rejected
- Malformed date strings not matching YYYY-MM-DD pattern cause schema validation failure
- Numeric values outside the allowed range (-1,000,000,000,000 to 1,000,000,000,000) are rejected
- Empty rows array (minItems: 1) returns an error
- Payment of 0.01 USDC not completed causes request to fail with 402

## How this service works

Company filing inventories — Record quality audit + String normalisation: Record quality audit + String normalisation for supplied company filing inventories records (available_filings, expected_filings). Up to 200 rows; 2 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 2 supplied-data reports for up to 200 rows.

## Output

Two independent reports: (1) a record quality audit covering issues such as nulls, out-of-range values, formatting errors, and anomalies across the available_filings and expected_filings numeric fields and date/string fields; (2) a string normalisation report showing standardised or corrected versions of string fields like company_group. Both reports are generated from the supplied data using local analytical engines with no external lookups.

## 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
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/company-filing-inventories-record-quality-audit-string-normalisation-bc0a8945/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)