# Time Series Completeness — Numeric Distribution + Base-100 Series

> Time Series Completeness — Numeric Distribution + Base-100 Series is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-15).

Analyzes time series completeness records (observed vs expected data points) by generating both a numeric distribution report and a base-100 rebase series for up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-16-078?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-15
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/time-series-completeness-numeric-distribution-base-100-series-31c33b9d
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_uSA-EgQJz--1y7v90QxAw

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-numeric-distribution-base-100-series-31c33b9d -d '<json body>'
```

Example prompt: I have daily time series completeness data for two groups over October 2026 — can you run a numeric distribution report AND a base-100 series rebased from index 0 on the observed_points field? Here are the rows: group-a on 2026-10-01 had 10 observed out of 1 expected, group-b on 2026-10-02 had 20 observed out of 2 expected, group-a on 2026-10-03 had 15 observed out of 3 expected, group-b on 2026-10-04 had 30 observed out of 4 expected.

## When to prefer this

Choose this endpoint when you need two complementary statistical views — a numeric distribution AND a base-100 indexed series — of time series completeness data in a single low-cost call. It is ideal for data quality monitoring workflows where you want both a spread analysis and a normalized trend comparison from supplied data without any external lookups or live data fetching. Prefer it over single-report endpoints when you need both report types simultaneously for up to 200 rows.

## Known failure modes

- Input array is empty or exceeds 200 rows — validation error returned
- base_index value exceeds the number of supplied rows — out-of-range error
- required fields (row_id, date, observed_points, expected_points) missing from any row — schema validation failure
- date strings not in YYYY-MM-DD format — pattern validation error
- observed_points or expected_points outside allowed numeric range — validation error
- Payment of 0.01 USDC not settled via x402 — request rejected

## How this service works

Time series completeness — Numeric distribution + Base-100 series: Numeric distribution + Base-100 series 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 sharing the same input data: (1) a numeric distribution report showing the statistical spread (bins, frequencies, percentiles) of the selected field across all rows, and (2) a base-100 rebase series that re-indexes values relative to the specified base row, enabling trend comparison. Both reports cover up to 200 supplied rows with no external data lookup.

## 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"
  },
  "base_index": {
   "type": "integer",
   "default": 0,
   "maximum": 199,
   "minimum": 0
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/time-series-completeness-numeric-distribution-base-100-series-31c33b9d/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)