# Pipeline Durations Analytics — Numeric Distribution & Trailing Mean Series

> Pipeline Durations Analytics — Numeric Distribution & 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 2026-10-16).

Computes a numeric distribution and a trailing mean time series for pipeline duration metrics (run_seconds or processed_rows) from up to 200 supplied records.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-05-076?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-16
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/pipeline-durations-analytics-numeric-distribution-trailing-mean-series-c8fc3bf2
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_lcqZAbmzKBwTIibhzN8D_

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 pipeline-durations-analytics-numeric-distribution-trailing-mean-series-c8fc3bf2 -d '<json body>'
```

Example prompt: Analyze the distribution and trailing mean of run_seconds for my pipeline runs — here are 4 records: row-1 on 2026-10-01 group-a ran 10s processing 1 row, row-2 on 2026-10-02 group-b ran 20s processing 2 rows, row-3 on 2026-10-03 group-a ran 15s processing 3 rows, row-4 on 2026-10-04 group-b ran 30s processing 4 rows — use a window of 3.

## When to prefer this

Choose this endpoint when you already have pipeline duration data in hand and need both a numeric distribution and a trailing mean series computed locally without any external data lookups, predictions, or live connections. Ideal for post-run ETL analytics, performance auditing, or trend detection on up to 200 pipeline execution records at minimal cost ($0.01 USDC for both reports).

## Known failure modes

- Fewer than 1 row supplied returns an error
- More than 200 rows submitted exceeds the item limit
- Window size smaller than 2 or larger than 200 is rejected
- Malformed date strings not matching YYYY-MM-DD pattern fail validation
- Missing required fields (row_id, date, run_seconds, processed_rows, dataset_group) cause schema errors
- Invalid field enum value (not run_seconds or processed_rows) returns an error

## How this service works

Pipeline durations — Numeric distribution + Trailing mean series: Numeric distribution + Trailing mean series for supplied pipeline durations records (run_seconds, processed_rows). 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 (histogram-style bin breakdown) of the selected field (run_seconds or processed_rows), and (2) a trailing mean time series computed over the specified rolling window — both derived from the supplied pipeline duration records using local analytical engines.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/pipeline-durations-analytics-numeric-distribution-trailing-mean-series-c8fc3bf2/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)