# Feature Availability Analytics — Exact Row Deduplication + Grouped Numeric Summary

> Feature Availability Analytics — Exact Row Deduplication + Grouped Numeric Summary 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).

Deduplicates exact duplicate rows and generates a grouped numeric summary report for feature availability records (populated_features, expected_features) across dataset groups and dates.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-10-040?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-exact-row-deduplication-grouped-fd822016
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_EIZ8zyNcqqltaYZ5_Hdyn

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-exact-row-deduplication-grouped-fd822016 -d '<json body>'
```

Example prompt: I have up to 200 feature availability records with populated_features and expected_features columns across several dataset groups — can you deduplicate the exact rows and give me a grouped numeric summary report for the populated_features field?

## When to prefer this

Choose this endpoint when you need both exact-row deduplication and a grouped numeric summary in a single call for up to 200 feature availability records — particularly when your data tracks populated vs expected feature counts across named dataset groups and dates, and you want a cheap ($0.01 USDC), local, offline computation with no external data enrichment or prediction.

## Known failure modes

- Input array is empty (minItems: 1 violated)
- More than 200 rows submitted (maxItems: 200 exceeded)
- row_id missing or blank (minLength: 1 violated)
- date field does not match YYYY-MM-DD pattern
- numeric field values exceed allowed range (±1,000,000,000,000)
- Invalid field enum value (must be populated_features or expected_features)
- Payment of 0.01 USDC not fulfilled via x402 protocol

## How this service works

Feature availability — Exact row deduplication + Grouped numeric summary: Exact row deduplication + Grouped numeric summary 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

Returns two independent analytical reports: (1) a deduplicated list of exact row matches removed from the input, and (2) a grouped numeric summary of the selected field (populated_features or expected_features) aggregated by dataset_group — all computed locally with no 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-exact-row-deduplication-grouped-fd822016/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)