# Transaction Fee Observations — Grouped Numeric Summary + Two-Measure Correlation

> Transaction Fee Observations — Grouped Numeric Summary + Two-Measure Correlation 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 up to 200 rows of transaction fee observation records by producing a grouped numeric summary and a two-measure correlation report for fee_units and transaction_count.

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-finance-03-095?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/transaction-fee-observations-grouped-numeric-summary-two-measure-0cabe4c4
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_JlLqI4S0FfWcb9Da1YT0v

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 transaction-fee-observations-grouped-numeric-summary-two-measure-0cabe4c4 -d '<json body>'
```

Example prompt: Can you run a grouped numeric summary and correlation analysis on my transaction fee data — I have records with instrument groups like 'equities' and 'derivatives', dates, fee_units, and transaction_count fields, up to 150 rows — and tell me how fee_units correlates with transaction_count?

## When to prefer this

Choose this endpoint when you have a dataset of transaction fee records (up to 200 rows) with instrument group labels and need both grouped descriptive statistics and a correlation between two numeric measures (fee_units and transaction_count) in a single low-cost call. It is purpose-built for finance/fee analytics with a fixed schema and requires no live market data or external lookups. Prefer it over general-purpose analytics APIs when you want a fast, cheap, deterministic computation on supplied data.

## Known failure modes

- Input array exceeds 200 rows — request will be rejected
- Missing required fields (row_id, instrument_group, date, fee_units, transaction_count) on any row cause validation errors
- Date field does not match YYYY-MM-DD pattern — schema validation failure
- Numeric values outside [-1000000000000, 1000000000000] range cause schema rejection
- Insufficient data variance for meaningful correlation (e.g. all identical values) may yield degenerate correlation output
- Payment of 0.01 USDC not completed — endpoint returns 402 error

## How this service works

Transaction fee observations — Grouped numeric summary + Two-measure correlation: Grouped numeric summary + Two-measure correlation for supplied transaction fee observations records (fee_units, transaction_count). 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 sharing a local engine: (1) a grouped numeric summary breaking down fee_units or transaction_count statistics by instrument_group, and (2) a two-measure correlation report between fee_units and transaction_count across the supplied rows. No live data lookup or external calls are made; all analysis is performed on the user-supplied dataset of up to 200 rows.

## Request schema (JSON Schema)

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

## More

- Live health (JSON, refreshed every minute): https://www.zero.xyz/c/transaction-fee-observations-grouped-numeric-summary-two-measure-0cabe4c4/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)