# Pipeline Durations — Record Quality Audit + String Normalisation + IQR Outlier Flags

> Pipeline Durations — Record Quality Audit + String Normalisation + IQR Outlier Flags 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 analytical reports on supplied pipeline duration records: a record quality audit, string normalisation, and IQR-based outlier flagging for run_seconds or processed_rows fields.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-05-203?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-record-quality-audit-string-normalisation-iqr-9a45dbe7
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_MWi7AK64eFw9dUyOf-Xuw

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-record-quality-audit-string-normalisation-iqr-9a45dbe7 -d '<json body>'
```

Example prompt: Can you run a quality audit, string normalisation, and IQR outlier check on my pipeline duration records? I have up to 50 rows with fields like run_seconds and processed_rows — flag any outliers and quality issues in the run_seconds field.

## When to prefer this

Choose this endpoint when you need a fast, offline, multi-report analytical pass over pipeline duration records without external lookups or predictions. Ideal for data engineering teams who want quality auditing, string normalisation, and statistical outlier detection (IQR method) bundled in a single cheap call for batches up to 200 rows.

## Known failure modes

- More than 200 rows submitted — request rejected
- Missing required fields (row_id, date, run_seconds, processed_rows) — validation error
- Invalid date format (not YYYY-MM-DD) — schema validation failure
- Invalid field selector (not run_seconds or processed_rows) — enum error
- Empty rows array — rejected with minItems violation

## How this service works

Pipeline durations — Record quality audit + String normalisation + IQR outlier flags: Record quality audit + String normalisation + IQR outlier flags 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 supplied rows: (1) a record quality audit identifying missing, malformed, or invalid values; (2) string normalisation results for text fields like dataset_group; and (3) IQR-based outlier flags identifying statistically anomalous values in the chosen numeric field (run_seconds or processed_rows). Up to 200 rows per call.

## 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"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/pipeline-durations-record-quality-audit-string-normalisation-iqr-9a45dbe7/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)