# Feature Availability Analytics — Numeric Distribution & Base-100 Series

> Feature Availability Analytics — Numeric Distribution & Base-100 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 numeric distribution report and a base-100 indexed time series for supplied feature availability data (populated_features vs expected_features) across up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-10-078?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-base-100-series-734c95b0
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_xa1J4p98wVWPFsLjMm84N

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-base-100-series-734c95b0 -d '<json body>'
```

Example prompt: Can you run a numeric distribution and base-100 series analysis on my feature availability data — I have 50 rows with populated_features and expected_features per date and dataset group, and I want the series indexed from row 0 on the populated_features field?

## When to prefer this

Use this endpoint when you have tabular feature availability data (populated vs expected feature counts per date and group) and need both a statistical distribution and a base-100 indexed trend series in a single low-cost call. Prefer this over general-purpose analytics tools when you want a lightweight, deterministic, offline computation with no data leaving your supplied payload to external sources, and when your dataset fits within 200 rows.

## Known failure modes

- Missing required fields (row_id, date, populated_features, expected_features) cause validation errors
- More than 200 rows submitted exceeds the maxItems limit and will be rejected
- Invalid date format (not YYYY-MM-DD) causes schema validation failure
- base_index out of range (>=number of rows) causes an error
- null values in both populated_features and expected_features may degrade or skip distribution calculations
- Payment of 0.01 USDC not attached causes 402 payment required response

## How this service works

Feature availability — Numeric distribution + Base-100 series: Numeric distribution + Base-100 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

Returns two independent analytical reports: (1) a numeric distribution summarizing the statistical spread of the selected field (populated_features or expected_features) across the submitted rows, and (2) a base-100 indexed time series showing relative movement from the chosen base_index row — both computed locally from the supplied data 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"
  },
  "base_index": {
   "type": "integer",
   "default": 0,
   "maximum": 199,
   "minimum": 0
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/feature-availability-analytics-numeric-distribution-base-100-series-734c95b0/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)