# Feature Availability Analytics — Numeric Distribution & Daily Sum Series

> Feature Availability Analytics — Numeric Distribution & 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 numeric distribution statistics and daily sum time series for feature availability data (populated_features, expected_features) across up to 200 rows, returning two independent analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-10-075?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-numeric-distribution-daily-sum-series-a4525bc2
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_ZyUw-bkXt4LC8KAtrh-yX

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-numeric-distribution-daily-sum-series-a4525bc2 -d '<json body>'
```

Example prompt: Analyze my feature availability data — I have 4 rows with dates from 2026-10-01 to 2026-10-04, dataset groups 'group-a' and 'group-b', and I want both the numeric distribution and daily sum series reports for the populated_features field.

## When to prefer this

Choose this endpoint when you have up to 200 feature availability records with populated/expected counts by date and group, and need both a distribution breakdown and a daily aggregate time series in one call at minimal cost ($0.01 USDC). It is a self-contained local analytics engine — ideal when you do not need live data lookup, predictions, or external enrichment, just statistical summaries of your own supplied data.

## Known failure modes

- Rows array is empty or missing — returns validation error
- More than 200 rows submitted — rejected with max-items error
- Date field does not match YYYY-MM-DD pattern — schema validation failure
- populated_features or expected_features values outside ±1,000,000,000,000 — rejected
- Invalid field enum value (not 'populated_features' or 'expected_features') — schema error
- Payment not processed — 402 response with no report returned

## How this service works

Feature availability — Numeric distribution + Daily sum series: Numeric distribution + 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 independent analytical reports: (1) a numeric distribution report summarizing the statistical spread (e.g. min, max, mean, percentiles, histogram-style bins) of the selected feature field, and (2) a daily sum series aggregating the selected field's totals by date — both computed locally from the supplied rows with no external data access.

## 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-numeric-distribution-daily-sum-series-a4525bc2/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)