# Time Series Completeness — Grouped Numeric Summary + Numeric Interval Filter

> Time Series Completeness — Grouped Numeric Summary + Numeric Interval Filter is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-28).

Analyzes time series completeness records (observed vs. expected data points) with grouped numeric summaries and interval filtering across up to 200 rows, producing two independent analytical reports.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-16-088?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-28
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/time-series-completeness-grouped-numeric-summary-numeric-interval-35e11da5
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_2TvXFRdp693mrU50fu27A

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-grouped-numeric-summary-numeric-interval-35e11da5 -d '<json body>'
```

Example prompt: I have completeness records for two dataset groups — group-a and group-b — with dates from 2026-10-01 to 2026-10-04 and observed/expected point counts. Can you give me a grouped numeric summary and also filter by observed_points between 0 and 25?

## When to prefer this

Choose this endpoint when you have pre-collected time series completeness records (observed vs. expected data points) and need both a grouped statistical summary by dataset group and an interval-filtered view in a single low-cost call. Ideal for data quality audits, pipeline monitoring dashboards, and completeness reporting where data is already available locally and no live lookup or external enrichment is needed. Best for batch sizes up to 200 rows at $0.01 per call.

## Known failure modes

- Input array exceeds 200 rows — request rejected
- Missing required fields (row_id, dataset_group, date, observed_points, or expected_points) — validation error
- Date field does not match YYYY-MM-DD pattern — schema validation failure
- Numeric values exceed allowed range (±1,000,000,000,000) — validation error
- Minimum greater than maximum for interval filter — may return empty filtered report
- Empty rows array — rejected by minItems constraint

## How this service works

Time series completeness — Grouped numeric summary + Numeric interval filter: Grouped numeric summary + Numeric interval filter 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 grouped numeric summary aggregating observed_points and expected_points statistics by dataset_group, and (2) a numeric interval filter report showing only rows where the selected field (observed_points or expected_points) falls within the specified minimum–maximum range. Results cover 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"
  },
  "maximum": {
   "type": "number",
   "default": 100,
   "maximum": 1000000000000,
   "minimum": -1000000000000
  },
  "minimum": {
   "type": "number",
   "default": 0,
   "maximum": 1000000000000,
   "minimum": -1000000000000
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/time-series-completeness-grouped-numeric-summary-numeric-interval-35e11da5/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)