# Feature Availability Analytics — Grouped Numeric Summary + Daily Sum Series

> Feature Availability Analytics — Grouped Numeric Summary + Daily Sum Series 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).

Computes a grouped numeric summary and a daily sum time series for feature availability data (populated_features, expected_features) across up to 200 rows, returning two local analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-10-089?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-grouped-numeric-summary-daily-sum-series-186a22c5
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_nMtlqcmLRqB9P8lymRq3M

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-grouped-numeric-summary-daily-sum-series-186a22c5 -d '<json body>'
```

Example prompt: I have a dataset with feature availability records — can you run a grouped numeric summary and daily sum series on my rows for the 'populated_features' field? I have 4 rows: row-1 for group-a on 2026-10-01 with populated=10 and expected=1, row-2 for group-b on 2026-10-02 with populated=20 and expected=2, row-3 for group-a on 2026-10-03 with populated=15 and expected=3, and row-4 for group-b on 2026-10-04 with populated=30 and expected=4.

## When to prefer this

Choose this endpoint when you have feature availability records (populated and expected feature counts) tagged by date and dataset group, and you need both a grouped statistical summary and a daily aggregated time series in a single cheap call ($0.01 USDC for up to 200 rows). Prefer this over general-purpose analytics tools when the data is already structured with populated_features/expected_features fields and you want two complementary views — cross-group statistics and a time trend — without spinning up a full analytics pipeline.

## Known failure modes

- Input array is empty or missing (minItems: 1 not satisfied)
- More than 200 rows supplied (maxItems: 200 exceeded)
- row_id missing or empty string (minLength: 1 required)
- date field does not match YYYY-MM-DD pattern
- field value is not one of the two allowed enum values ('populated_features' or 'expected_features')
- populated_features or expected_features exceed numeric bounds (±1,000,000,000,000)
- Malformed JSON body returns validation error

## How this service works

Feature availability — Grouped numeric summary + Daily sum series: Grouped numeric summary + Daily sum series 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 analytical reports: (1) a grouped numeric summary breaking down populated_features or expected_features statistics by dataset_group, and (2) a daily sum time series aggregating the selected field by date — computed locally on the supplied rows with no external calls.

## 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-grouped-numeric-summary-daily-sum-series-186a22c5/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)