# Null Coverage Analytics — Base-100 Series + IQR Outlier Flags

> Null Coverage Analytics — Base-100 Series + IQR Outlier Flags is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-18).

Computes a base-100 indexed time series and IQR-based outlier flags for user-supplied null coverage data (missing_values, total_values) across up to 200 rows, delivering two analytical reports per call.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-03-164?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-18
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/null-coverage-analytics-base-100-series-iqr-outlier-flags-9968a6db
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_kfqzONBmURShE04v8oaps

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-base-100-series-iqr-outlier-flags-9968a6db -d '<json body>'
```

Example prompt: I have a set of null coverage records — up to 50 rows with date, dataset_group, missing_values, and total_values — can you compute a base-100 indexed series starting from index 0 on the missing_values field, and flag any IQR outliers in the data?

## When to prefer this

Choose this endpoint when you have pre-collected null coverage or data completeness records and need both a normalized trend index and statistical outlier detection in a single low-cost call. It is ideal for data quality audits, ETL monitoring, and completeness reporting workflows where all data is already available locally and no live lookup, prediction, or external enrichment is needed.

## Known failure modes

- Missing required fields (row_id, date, missing_values, total_values) cause validation errors
- Date strings not matching YYYY-MM-DD pattern are rejected
- Array exceeding 200 rows is rejected with a maxItems error
- base_index out of range (0–199) causes a validation error
- null values in missing_values or total_values may affect IQR computation depending on implementation
- Payment failure via x402 protocol returns 402 before processing

## How this service works

Null coverage — Base-100 series + IQR outlier flags: Base-100 series + IQR outlier flags 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 base-100 indexed time series for the selected field (missing_values or total_values) anchored at the specified base_index row, and (2) IQR-based outlier flags marking which rows fall outside the interquartile range, all computed locally without external data lookups or predictions.

## 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-base-100-series-iqr-outlier-flags-9968a6db/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)