# Pipeline Durations Analytics — Record Quality Audit, String Normalisation & Category Frequencies

> Pipeline Durations Analytics — Record Quality Audit, String Normalisation & Category Frequencies 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).

Runs three local analytical reports on pipeline duration records: record quality audit, string normalisation, and category frequency analysis for up to 200 rows of run_seconds and processed_rows data.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-05-195?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/pipeline-durations-analytics-record-quality-audit-string-29ac8d00
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_KVJZZRwOsy0y_vBcdEHZS

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-record-quality-audit-string-29ac8d00 -d '<json body>'
```

Example prompt: Can you audit the quality of these pipeline duration records, normalise the dataset_group strings, and give me category frequencies? I have 4 rows: row-1 on 2026-10-01, group-a, 10 seconds, 1 row processed; row-2 on 2026-10-02, group-b, 20 seconds, 2 rows; row-3 on 2026-10-03, group-a, 15 seconds, 3 rows; row-4 on 2026-10-04, group-b, 30 seconds, 4 rows.

## When to prefer this

Choose this endpoint when you need a combined data quality audit, string normalisation, and category frequency analysis for pipeline duration records (run_seconds, processed_rows) in a single cheap call. It is purpose-built for ETL/pipeline log data with up to 200 rows and delivers three reports at once for $0.01 USDC, making it ideal for lightweight, local analytical profiling without any external data lookups or predictions.

## Known failure modes

- Rows array empty or missing — validation error
- More than 200 rows submitted — rejected with max-items error
- run_seconds or processed_rows outside allowed numeric range — schema rejection
- date field not matching YYYY-MM-DD pattern — schema rejection
- row_id missing or empty — validation error
- Payment not provided or insufficient — x402 payment required response

## How this service works

Pipeline durations — Record quality audit + String normalisation + Category frequencies: Record quality audit + String normalisation + Category frequencies for supplied pipeline durations records (run_seconds, processed_rows). Up to 200 rows; 3 independent reports using shared local analytical engines. No live lookup, prediction, professional assessment or external action. 0.01 USDC includes 3 supplied-data reports for up to 200 rows.

## Output

Returns three independent analytical reports for the submitted pipeline duration rows: (1) a record quality audit flagging nulls, out-of-range values, and malformed fields; (2) a string normalisation report cleaning dataset_group and date strings; (3) a category frequency table showing how often each dataset_group appears. All computed locally with no external lookups.

## 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
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/pipeline-durations-analytics-record-quality-audit-string-29ac8d00/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)