# Feature Availability Analytics — Duplicate Key Report + Numeric Distribution

> Feature Availability Analytics — Duplicate Key Report + 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 2026-10-20).

Analyzes up to 200 feature availability records to produce two independent reports: a duplicate key report and a numeric distribution for populated_features or expected_features.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-10-055?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/feature-availability-analytics-duplicate-key-report-numeric-b26706b7
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_JSOb-JyO96S6opCPcLpKG

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 feature-availability-analytics-duplicate-key-report-numeric-b26706b7 -d '<json body>'
```

Example prompt: I have 50 feature availability records with row_id, dataset_group, date, populated_features, and expected_features — can you run a duplicate key report and numeric distribution on the populated_features field for me?

## When to prefer this

Choose this endpoint when you need simultaneous duplicate-key detection and numeric distribution analysis on a single batch of feature availability records (up to 200 rows) at low cost ($0.01 USDC for both reports). It is ideal for data quality audits before ML pipelines, ETL validation, or feature store monitoring where both duplication and value spread are relevant. Prefer alternatives if you need live data lookups, predictions, more than 200 rows, or reports beyond duplicate detection and numeric distribution.

## Known failure modes

- Submitting more than 200 rows causes rejection
- Missing required fields (row_id, date, populated_features, expected_features) causes validation error
- Date values not matching YYYY-MM-DD pattern are rejected
- Numeric values outside the allowed range (-1,000,000,000,000 to 1,000,000,000,000) are rejected
- Empty rows array causes failure
- Invalid field enum value (not populated_features or expected_features) causes error

## How this service works

Feature availability — Duplicate key report + Numeric distribution: Duplicate key report + Numeric distribution for supplied feature availability records (populated_features, expected_features). 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 analytical reports: (1) a duplicate key report identifying repeated row_id values within the submitted rows, and (2) a numeric distribution summarizing the spread and frequency of values in the selected field (populated_features or expected_features), all computed locally on the supplied data without any external lookups.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "rows": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "row_id",
     "dataset_group",
     "date",
     "populated_features",
     "expected_features"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "maxLength": 10
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "dataset_group": {
      "type": "string",
      "default": "",
      "maxLength": 80
     },
     "expected_features": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "populated_features": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "dataset_group": "group-a",
     "expected_features": 1,
     "populated_features": 10
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "dataset_group": "group-b",
     "expected_features": 2,
     "populated_features": 20
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "dataset_group": "group-a",
     "expected_features": 3,
     "populated_features": 15
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "dataset_group": "group-b",
     "expected_features": 4,
     "populated_features": 30
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "populated_features",
    "expected_features"
   ],
   "type": "string",
   "default": "populated_features"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/feature-availability-analytics-duplicate-key-report-numeric-b26706b7/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)