# Data Freshness Record Quality Audit + Trailing Mean Series

> Data Freshness Record Quality Audit + 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 2026-10-19).

Runs two analytical reports—a record quality audit and a trailing mean series—on supplied data freshness records (age_minutes and record_count fields), returning local analytics with no external lookups.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-06-010?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-19
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/data-freshness-record-quality-audit-trailing-mean-series-feff5d2b
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_rFwkTcg6o42KxBQGQLtyu

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-record-quality-audit-trailing-mean-series-feff5d2b -d '<json body>'
```

Example prompt: Can you run a record quality audit and trailing mean series on my data freshness records? Here are up to 200 rows with row_id, dataset_group, date, age_minutes, and record_count — use age_minutes as the field with a window of 3.

## When to prefer this

Choose this endpoint when you need two combined analytical reports—quality audit and trailing mean—on data freshness records in a single low-cost call, without requiring any external data lookup, live prediction, or professional assessment. It is especially suited for monitoring data pipeline freshness metrics (age_minutes, record_count) across dataset groups over time, and for lightweight batch analysis of up to 200 rows at $0.01 per call.

## Known failure modes

- Fewer than 1 row supplied returns a validation error
- More than 200 rows supplied exceeds the row limit and is rejected
- Window size larger than number of rows may yield empty or partial trailing mean series
- Invalid date format (not YYYY-MM-DD) causes schema validation failure
- Missing required fields (row_id, dataset_group, date) cause request rejection
- Non-numeric values in age_minutes or record_count outside the allowed range cause errors

## How this service works

Data freshness — Record quality audit + Trailing mean series: Record quality audit + Trailing mean series 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 analytical reports: (1) a record quality audit that flags issues, anomalies, or quality signals in the supplied freshness records; and (2) a trailing mean series showing rolling averages over the specified window for the chosen field (age_minutes or record_count), all computed locally without external lookups.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "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-record-quality-audit-trailing-mean-series-feff5d2b/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)