# Feature Availability Analytics — Daily Sum + Trailing Mean Series

> Feature Availability Analytics — Daily Sum + Trailing Mean 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 daily sum series and trailing mean series for feature availability records (populated_features and expected_features) from user-supplied row data, returning two analytical reports in one call.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-10-136?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-daily-sum-trailing-mean-series-cd58a2b2
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_buzMHcl0wsJZ7nzgANwAr

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-daily-sum-trailing-mean-series-cd58a2b2 -d '<json body>'
```

Example prompt: I have 50 rows of feature availability data with populated_features and expected_features values per date and dataset group — can you run a daily sum series and a trailing mean series with a window of 7 on the populated_features field and give me both reports?

## When to prefer this

Choose this endpoint when you need a dual analytical report — both daily sum series and trailing mean series — computed entirely from locally supplied feature availability data in a single low-cost call. Ideal when you already have structured row data with populated_features and expected_features fields and want fast, offline-style aggregation without external data lookups or prediction services. Prefer this over general analytics APIs when you need feature availability-specific metrics at $0.01 per call for up to 200 rows.

## Known failure modes

- Fewer than 1 row supplied — minimum 1 row required
- More than 200 rows supplied — maxItems limit exceeded
- Invalid date format (must match YYYY-MM-DD pattern)
- Window size below 2 or above 200 — out of allowed range
- Non-numeric or out-of-range values in populated_features or expected_features
- Missing required fields (row_id, dataset_group, date) in any row
- Unknown field enum value (must be populated_features or expected_features)

## How this service works

Feature availability — Daily sum series + Trailing mean series: Daily sum series + Trailing mean 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 analytical reports: (1) a daily sum series aggregating the selected field (populated_features or expected_features) by date, and (2) a trailing mean series computed over the specified window size — both derived from the supplied row data, up to 200 rows, with no external lookups or live data.

## 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"
  },
  "window": {
   "type": "integer",
   "default": 2,
   "maximum": 200,
   "minimum": 2
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/feature-availability-analytics-daily-sum-trailing-mean-series-cd58a2b2/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)