# Time Series Completeness — Record Quality Audit + Two-Measure Correlation

> Time Series Completeness — Record Quality Audit + Two-Measure Correlation is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-24).

Audits record quality and computes two-measure correlation for time series completeness data (observed vs expected data points), processing up to 200 rows and returning two independent analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-16-015?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-24
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/time-series-completeness-record-quality-audit-two-measure-correlation-8ac1a709
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_JYr9dmXuPPZ-5gvWW_R3x

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 time-series-completeness-record-quality-audit-two-measure-correlation-8ac1a709 -d '<json body>'
```

Example prompt: Can you run a record quality audit and correlation report on my time series completeness data? I have rows from 2026-10-01 through 2026-10-04 with dataset groups 'group-a' and 'group-b', showing observed_points like 10, 20, 15, 30 against expected_points of 1, 2, 3, 4 — send it all in and give me both reports.

## When to prefer this

Choose this endpoint when you need both a data quality audit and a correlation analysis on time series completeness records in a single $0.01 call, without requiring any live data lookup, external enrichment, or predictive modeling. Ideal for batch validation of up to 200 rows of observed vs expected data point counts grouped by dataset and date.

## Known failure modes

- Exceeding 200 row limit causes rejection
- Missing required fields (row_id, date, observed_points, expected_points) causes validation error
- Invalid date format (not YYYY-MM-DD) causes schema rejection
- Payment failure or insufficient USDC balance blocks processing
- Null values in observed_points or expected_points may reduce correlation reliability

## How this service works

Time series completeness — Record quality audit + Two-measure correlation: Record quality audit + Two-measure correlation for supplied time series completeness records (observed_points, expected_points). 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 record quality audit covering the completeness records (flagging anomalies, nulls, or out-of-range values in observed_points and expected_points), and (2) a two-measure correlation analysis between observed_points and expected_points across the supplied time series rows. No external lookups or predictions are performed; all analysis is based solely on the supplied data.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/time-series-completeness-record-quality-audit-two-measure-correlation-8ac1a709/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)