# Job Listing Inventories — Record Quality Audit + String Normalisation + Numeric Distribution

> Job Listing 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 2026-10-25).

Runs three local analytical reports (record quality audit, string normalisation, and numeric distribution) on up to 200 rows of job listing inventory data containing listing counts and duplicate listing counts.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-company-13-193?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-25
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/job-listing-inventories-record-quality-audit-string-normalisation-564a39a8
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_7kIYmYEUvgytdrQLYBRA9

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 job-listing-inventories-record-quality-audit-string-normalisation-564a39a8 -d '<json body>'
```

Example prompt: Can you run a record quality audit, string normalisation, and numeric distribution analysis on my job listing inventory data — I have rows with company_group, date, listing_count, and duplicate_listings fields, and I want to analyse the listing_count field specifically? Here are my rows: [{"row_id":"r1","company_group":"Acme Corp","date":"2024-01-15","listing_count":120,"duplicate_listings":5},{"row_id":"r2","company_group":"Beta Inc","date":"2024-01-16","listing_count":null,"duplicate_listings":3}].

## When to prefer this

Choose this endpoint when you need three simultaneous local data quality and profiling reports on job listing inventory records without any live data lookup or external enrichment. It is ideal for pre-processing pipeline validation, data cleaning workflows, or quick exploratory data profiling on batches of up to 200 rows. Prefer this over general-purpose analytics tools when you specifically need all three report types (quality audit, string normalisation, numeric distribution) in a single cheap call ($0.01 USDC) for the job listings domain.

## Known failure modes

- More than 200 rows submitted — request will be rejected or truncated
- Missing required fields (row_id, company_group, date, listing_count, duplicate_listings) cause validation errors
- Invalid date format (not YYYY-MM-DD) triggers schema validation failure
- field selector not one of the allowed enum values ('listing_count' or 'duplicate_listings') causes rejection
- All-null numeric field may produce empty or degenerate distribution report
- Empty rows array rejected (minItems: 1)

## How this service works

Job listing inventories — Record quality audit + String normalisation + Numeric distribution: Record quality audit + String normalisation + Numeric distribution for supplied job listing inventories records (listing_count, duplicate_listings). 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 delivered together: (1) a record quality audit flagging missing values, invalid formats, and outliers; (2) a string normalisation report highlighting inconsistencies in text fields like company_group; (3) a numeric distribution report (min, max, mean, percentiles, etc.) for the selected numeric field (listing_count or duplicate_listings). All analysis is performed locally on the supplied rows with no external lookups.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/job-listing-inventories-record-quality-audit-string-normalisation-564a39a8/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)