# Company Filing Inventories — Record Quality Audit, String Normalisation & Daily Sum Series

> Company Filing Inventories — Record Quality Audit, String Normalisation & Daily Sum Series 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 on company filing inventory data: a record quality audit, string normalisation, and a daily sum series — no external lookups.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-company-17-198?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-d10411dd
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_bzBugagVwGnOyoj3JWunE

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-d10411dd -d '<json body>'
```

Example prompt: Can you run a record quality audit, string normalisation, and daily sum series on my company filing inventory data? I have rows with row_id, company_group, date, available_filings, and expected_filings — up to 50 rows — and I want to focus the sum series on available_filings.

## When to prefer this

Choose this endpoint when you have up to 200 rows of company filing inventory data and need three bundled local analytical reports — quality audit, string normalisation, and daily aggregation — in a single cost-effective call ($0.01 USDC). Prefer it over bespoke data pipelines when you want fast, offline-style analysis without any external lookups, predictions, or professional assessments. Best suited for compliance teams, data engineers, or agents that need to validate and summarise filing inventory data before downstream processing.

## Known failure modes

- Empty or missing rows array returns validation error
- More than 200 rows causes rejection due to row limit
- Invalid date format (not YYYY-MM-DD) triggers pattern validation failure
- Numeric values outside ±1,000,000,000,000 range are rejected
- Missing required fields (row_id, date, company_group, available_filings, expected_filings) cause schema errors
- Invalid field enum value (not available_filings or expected_filings) returns error

## How this service works

Company filing inventories — Record quality audit + String normalisation + Daily sum series: Record quality audit + String normalisation + Daily sum series 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 supplied dataset: (1) a record quality audit flagging missing, malformed, or out-of-range values; (2) a string normalisation report cleaning company_group and other text fields; and (3) a daily sum series aggregating the chosen numeric field (available_filings or expected_filings) by date — all computed locally with no external data 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
  },
  "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-d10411dd/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)