# Data Freshness Analytics: Trailing Mean Series + Equal-Width Histogram

> Data Freshness Analytics: Trailing Mean Series + Equal-Width Histogram is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-18).

Computes a trailing moving-average time series and an equal-width frequency histogram for data freshness records (age_minutes, record_count) supplied by the caller — no external lookups, up to 200 rows, two reports per call.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-06-148?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-18
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/data-freshness-analytics-trailing-mean-series-equal-width-histogram-d69d6c65
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_RML3oG9lE8EYzEnpVV_5V

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 data-freshness-analytics-trailing-mean-series-equal-width-histogram-d69d6c65 -d '<json body>'
```

Example prompt: I have 50 daily freshness records for two dataset groups — each with a date, age_minutes, and record_count — can you run a trailing mean series with a window of 7 and a 10-bin equal-width histogram on the age_minutes field for me?

## When to prefer this

Choose this endpoint when you have up to 200 pre-collected data freshness records and need both a smoothed time-series trend (trailing mean) and a distribution summary (histogram) in a single low-cost call. It is ideal for offline or batch analytical reporting on data pipeline health where no live data lookup, prediction, or external enrichment is needed. Prefer alternatives if you need real-time freshness checks, ML-based anomaly detection, or more than 200 rows.

## Known failure modes

- Fewer than 1 row supplied — request rejected
- More than 200 rows supplied — request rejected
- Invalid date format (not YYYY-MM-DD) — validation error
- Window size larger than number of rows — trailing mean may be empty or partial
- Bins parameter outside 1–30 range — validation error
- Null values in age_minutes or record_count — rows may be skipped or treated as missing

## How this service works

Data freshness — Trailing mean series + Equal-width histogram: Trailing mean series + Equal-width histogram for supplied data freshness records (age_minutes, record_count). 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 sharing the same input data: (1) a trailing mean series showing the rolling average of the selected field (age_minutes or record_count) over the specified window, and (2) an equal-width histogram summarizing the frequency distribution of the field across the specified number of bins. No external data is fetched; all computation is performed locally on the supplied rows.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "bins": {
   "type": "integer",
   "default": 5,
   "maximum": 30,
   "minimum": 1
  },
  "rows": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "row_id",
     "dataset_group",
     "date",
     "age_minutes",
     "record_count"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "maxLength": 10
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "age_minutes": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "record_count": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "dataset_group": {
      "type": "string",
      "default": "",
      "maxLength": 80
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "age_minutes": 10,
     "record_count": 1,
     "dataset_group": "group-a"
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "age_minutes": 20,
     "record_count": 2,
     "dataset_group": "group-b"
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "age_minutes": 15,
     "record_count": 3,
     "dataset_group": "group-a"
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "age_minutes": 30,
     "record_count": 4,
     "dataset_group": "group-b"
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "age_minutes",
    "record_count"
   ],
   "type": "string",
   "default": "age_minutes"
  },
  "window": {
   "type": "integer",
   "default": 2,
   "maximum": 200,
   "minimum": 2
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/data-freshness-analytics-trailing-mean-series-equal-width-histogram-d69d6c65/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)