# Join Coverage Analytics: Category Frequencies + Base-100 Series

> Join Coverage Analytics: Category Frequencies + 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).

Computes category frequency distributions and a base-100 indexed time series for join coverage metrics (matched_rows, source_rows) across up to 200 supplied rows.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-analytics-09-105?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/join-coverage-analytics-category-frequencies-base-100-series-5bb46628
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_zfO4H0HMU30X5vV5QIxWF

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 join-coverage-analytics-category-frequencies-base-100-series-5bb46628 -d '<json body>'
```

Example prompt: Can you run the category frequency and base-100 series analysis on my join coverage data? I have 4 rows: 2026-10-01 group-a had 10 matched and 1 source, 2026-10-02 group-b had 20 matched and 2 source, 2026-10-03 group-a had 15 matched and 3 source, 2026-10-04 group-b had 30 matched and 4 source — use matched_rows as the field and index from row 0.

## When to prefer this

Choose this endpoint when you need dual analytical reports — category frequency distributions AND a base-100 indexed series — on join coverage data (matched_rows vs source_rows) in a single call. Ideal for data engineers auditing ETL pipeline join rates, reconciliation analysts comparing dataset completeness across groups over time, or anyone needing lightweight local analytics on up to 200 rows without live lookups or external dependencies. At $0.01 USDC for both reports simultaneously, it's cost-efficient for iterative pipeline monitoring.

## Known failure modes

- Missing required fields (row_id, date, dataset_group, matched_rows, source_rows) cause validation errors
- Date strings not matching YYYY-MM-DD pattern are rejected
- Exceeding 200 rows returns an error
- base_index out of range (0–199) is rejected
- Null values in matched_rows or source_rows may affect computation accuracy
- Payment failure via x402 protocol prevents processing

## How this service works

Join coverage — Category frequencies + Base-100 series: Category frequencies + Base-100 series for supplied join coverage records (matched_rows, source_rows). 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) category frequency counts showing how matched_rows or source_rows values distribute across dataset_group categories, and (2) a base-100 indexed time series normalizing the selected field relative to the specified base row, enabling trend comparison across dates and groups.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/join-coverage-analytics-category-frequencies-base-100-series-5bb46628/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)