# Job Listing Inventories — String Normalisation + IQR Outlier Flags

> Job Listing Inventories — String Normalisation + IQR Outlier Flags is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-11-02).

Normalises string fields and flags IQR-based outliers across listing_count and duplicate_listings fields in job listing inventory records (up to 200 rows, 2 reports).

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-company-13-032?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-11-02
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/job-listing-inventories-string-normalisation-iqr-outlier-flags-fe9f7868
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_xPZ14Id0WOfxhG15beYp9

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-string-normalisation-iqr-outlier-flags-fe9f7868 -d '<json body>'
```

Example prompt: Can you normalize the string fields and flag IQR outliers in my job listing inventory data? I have up to 200 rows with listing_count values per company group and date, and I want the analysis run on the listing_count field.

## When to prefer this

Choose this endpoint when you have job listing inventory records (with listing_count and/or duplicate_listings fields) and need both string normalisation and IQR-based statistical outlier detection in a single low-cost call. Ideal for pre-reporting data cleaning pipelines where you want to identify anomalous listing volumes without building custom statistical tooling. Best suited for datasets up to 200 rows where no live data lookup or predictive modelling is required.

## 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 (must match YYYY-MM-DD pattern) causes schema rejection
- Numeric values outside allowed range cause validation failure
- Insufficient data variance for meaningful IQR calculation may yield uninformative outlier flags

## How this service works

Job listing inventories — String normalisation + IQR outlier flags: String normalisation + IQR outlier flags for supplied job listing inventories records (listing_count, duplicate_listings). 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

Returns two analytical reports per call: (1) string normalisation output for the company_group and date string fields, and (2) IQR-based outlier flags for the selected numeric field (listing_count or duplicate_listings) across the supplied rows. No external lookups or predictions are made; all analysis is performed locally on the submitted data.

## 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-string-normalisation-iqr-outlier-flags-fe9f7868/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)