# Null Coverage Analytics: Numeric Distribution + Base-100 Series

> Null Coverage Analytics: 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 2026-10-16).

Computes numeric distribution statistics and a base-100 indexed series for supplied null coverage data (missing_values and total_values fields) across up to 200 rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-03-078?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-16
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/null-coverage-analytics-numeric-distribution-base-100-series-0b4fbb92
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_bLMVRexmk8WMPFirNan31

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 null-coverage-analytics-numeric-distribution-base-100-series-0b4fbb92 -d '<json body>'
```

Example prompt: I have null coverage records for two groups — 'group-a' and 'group-b' — with dates from 2026-10-01 to 2026-10-04 and their missing_values and total_values counts. Can you run a numeric distribution report and a base-100 series (starting from index 0) on the missing_values field for up to 4 rows?

## When to prefer this

Choose this endpoint when you have pre-collected null coverage records (missing_values, total_values) and need two reports — numeric distribution and a base-100 series — computed offline without any live data lookup. It is ideal for data quality monitoring pipelines, batch reporting on completeness metrics, and trend indexing tasks where up to 200 rows of grouped time-series data need local statistical analysis in a single low-cost call.

## Known failure modes

- Missing required fields (row_id, date, missing_values, total_values) cause validation errors
- Date values not matching YYYY-MM-DD pattern are rejected
- More than 200 rows submitted exceeds the maxItems limit
- null or out-of-range numeric values for missing_values or total_values may be flagged
- base_index out of range (0-199) causes an error
- Empty rows array is rejected

## How this service works

Null coverage — Numeric distribution + Base-100 series: Numeric distribution + Base-100 series for supplied null coverage records (missing_values, total_values). 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 numeric distribution breakdown of the selected field (missing_values or total_values) across the supplied rows, and (2) a base-100 indexed series anchored at the specified base_index row — both computed locally without any external lookups.

## Request schema (JSON Schema)

```json
{
 "type": "object",
 "properties": {
  "rows": {
   "type": "array",
   "items": {
    "type": "object",
    "required": [
     "row_id",
     "dataset_group",
     "date",
     "missing_values",
     "total_values"
    ],
    "properties": {
     "date": {
      "type": "string",
      "default": "",
      "pattern": "^\\d{4}-\\d{2}-\\d{2}$",
      "maxLength": 10
     },
     "row_id": {
      "type": "string",
      "default": "",
      "maxLength": 80,
      "minLength": 1
     },
     "total_values": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     },
     "dataset_group": {
      "type": "string",
      "default": "",
      "maxLength": 80
     },
     "missing_values": {
      "type": [
       "number",
       "null"
      ],
      "maximum": 1000000000000,
      "minimum": -1000000000000
     }
    },
    "additionalProperties": false
   },
   "default": [
    {
     "date": "2026-10-01",
     "row_id": "row-1",
     "total_values": 1,
     "dataset_group": "group-a",
     "missing_values": 10
    },
    {
     "date": "2026-10-02",
     "row_id": "row-2",
     "total_values": 2,
     "dataset_group": "group-b",
     "missing_values": 20
    },
    {
     "date": "2026-10-03",
     "row_id": "row-3",
     "total_values": 3,
     "dataset_group": "group-a",
     "missing_values": 15
    },
    {
     "date": "2026-10-04",
     "row_id": "row-4",
     "total_values": 4,
     "dataset_group": "group-b",
     "missing_values": 30
    }
   ],
   "maxItems": 200,
   "minItems": 1
  },
  "field": {
   "enum": [
    "missing_values",
    "total_values"
   ],
   "type": "string",
   "default": "missing_values"
  },
  "base_index": {
   "type": "integer",
   "default": 0,
   "maximum": 199,
   "minimum": 0
  }
 }
}
```

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/null-coverage-analytics-numeric-distribution-base-100-series-0b4fbb92/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)