# Company Record Completeness Audit — Record Quality, String Normalisation & Adjacent Row Changes

> Company Record Completeness Audit — Record Quality, String Normalisation & Adjacent Row Changes 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).

Runs three local analytical reports (record quality audit, string normalisation, and adjacent row changes) on up to 200 company completeness records containing populated_fields and required_fields metrics.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-company-01-200?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-record-completeness-audit-record-quality-string-normalisation-e992b141
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_RPVbQcaipKwhTi6W9Hmqe

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-record-completeness-audit-record-quality-string-normalisation-e992b141 -d '<json body>'
```

Example prompt: Can you run a record quality audit, string normalisation check, and adjacent row change analysis on these company completeness records — I have up to 50 rows with populated_fields and required_fields counts per company group, and I want the report on the populated_fields column?

## When to prefer this

Choose this endpoint when you have a batch of up to 200 company completeness records (with populated_fields and required_fields counts) and need all three analytical perspectives — quality audit, string normalisation, and adjacent row change detection — in a single low-cost call. It is ideal for offline, no-external-lookup audits where the data is already collected and you want structured diagnostic reports without any live enrichment or prediction. Prefer alternatives if you need real-time CRM lookups, ML-based anomaly scoring, or batch sizes exceeding 200 rows.

## Known failure modes

- Submitting more than 200 rows returns a validation error
- Missing required fields (row_id, company_group, date, populated_fields, required_fields) on any row causes rejection
- Invalid date format (not YYYY-MM-DD) triggers a 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 or missing rows property returns a bad request error
- Payment of 0.01 USDC not included or rejected results in a 402 Payment Required response

## How this service works

Company record completeness — Record quality audit + String normalisation + Adjacent row changes: Record quality audit + String normalisation + Adjacent row changes for supplied company record completeness records (populated_fields, required_fields). 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 flagging issues such as nulls, out-of-range values, and structural problems; (2) a string normalisation report identifying inconsistent or malformed string values in company_group and other text fields; and (3) an adjacent row changes report showing value differences between consecutive rows for the selected numeric field (populated_fields or required_fields). All processing is local — no external lookups or live data enrichment.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/company-record-completeness-audit-record-quality-string-normalisation-e992b141/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)