# Time Series Completeness — Duplicate Key Report + Secondary-Measure Weighted Mean

> Time Series Completeness — Duplicate Key Report + Secondary-Measure Weighted Mean 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).

Analyzes supplied time series completeness records to produce a duplicate key report and a secondary-measure weighted mean, using shared local analytical engines — no external lookups.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-16-067?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-duplicate-key-report-secondary-measure-b99ef39f
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_pRwnLgbLUG54s1eFu5a-z

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-duplicate-key-report-secondary-measure-b99ef39f -d '<json body>'
```

Example prompt: Can you run a duplicate key report and compute a weighted mean of observed_points for these completeness records — I have 4 rows with dates 2026-10-01 through 2026-10-04, row IDs row-1 to row-4, groups group-a and group-b, with observed_points 10, 20, 15, 30 and expected_points 1, 2, 3, 4?

## When to prefer this

Choose this endpoint when you need two simultaneous analytical operations on a batch of time series completeness records — duplicate key detection plus weighted mean computation — without any external data lookups or predictions. Ideal for data quality pipelines, ETL validation, and completeness monitoring workflows where you supply your own data (up to 200 rows) and need fast, local statistical analysis at low cost ($0.01 USDC for both reports).

## Known failure modes

- Input exceeds 200 rows — request rejected
- Missing required fields (row_id, date, observed_points, expected_points) — validation error
- Invalid date format not matching YYYY-MM-DD pattern — schema rejection
- Null values in numeric fields may affect weighted mean computation
- Empty rows array — minimum 1 item required

## How this service works

Time series completeness — Duplicate key report + Secondary-measure weighted mean: Duplicate key report + Secondary-measure weighted mean 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 duplicate key report identifying any rows with repeated key combinations, and (2) a weighted mean of the selected secondary measure (observed_points or expected_points) across the supplied rows — computed locally with no external data access, covering up to 200 input rows.

## 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
  },
  "field": {
   "enum": [
    "observed_points",
    "expected_points"
   ],
   "type": "string",
   "default": "observed_points"
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/time-series-completeness-duplicate-key-report-secondary-measure-b99ef39f/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)