# Feature Availability Analytics: Quality Audit + Deduplication + Interval Filter

> Feature Availability Analytics: Quality Audit + Deduplication + Interval Filter is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-19).

Runs three local analytical reports on feature availability records: record quality audit, exact row deduplication, and numeric interval filtering for populated_features or expected_features values.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-10-214?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-19
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/feature-availability-analytics-quality-audit-deduplication-interval-9c194c48
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_F8l2ZuHF355tNxl1nbq3f

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-quality-audit-deduplication-interval-9c194c48 -d '<json body>'
```

Example prompt: Can you run a quality audit, deduplication check, and filter for populated_features between 0 and 50 on these feature availability rows I have for group-a and group-b across October 2026?

## When to prefer this

Choose this endpoint when you have up to 200 feature availability records and need all three of: record quality auditing, exact duplicate detection, and numeric range filtering — in a single cost-efficient call ($0.01 USDC for all three reports). Ideal for ML/data engineering pipelines that need lightweight, self-contained analytics without external data lookups, predictions, or side effects. Not suitable for large datasets exceeding 200 rows, live data enrichment, or probabilistic deduplication.

## Known failure modes

- Rows array empty or missing — minimum 1 row required
- More than 200 rows submitted — batch size limit exceeded
- Invalid date format (must be YYYY-MM-DD)
- row_id missing or empty string — required field
- Numeric values for populated_features or expected_features out of allowed range (±1 trillion)
- minimum greater than maximum for interval filter — may return empty filter results
- field enum value not recognized — must be 'populated_features' or 'expected_features'
- Payment of 0.01 USDC not provided or rejected

## How this service works

Feature availability — Record quality audit + Exact row deduplication + Numeric interval filter: Record quality audit + Exact row deduplication + Numeric interval filter for supplied feature availability records (populated_features, expected_features). 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 computed locally from the supplied rows: (1) a record quality audit summarizing data completeness and anomalies across populated_features and expected_features, (2) an exact row deduplication report identifying and removing duplicate records, and (3) a numeric interval filter report returning only rows where the selected field (populated_features or expected_features) falls within the specified minimum–maximum range. All reports are derived from the input data only — no external lookups are performed.

## 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"
  },
  "maximum": {
   "type": "number",
   "default": 100,
   "maximum": 1000000000000,
   "minimum": -1000000000000
  },
  "minimum": {
   "type": "number",
   "default": 0,
   "maximum": 1000000000000,
   "minimum": -1000000000000
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/feature-availability-analytics-quality-audit-deduplication-interval-9c194c48/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)