# Transaction Fee Observations — Category Frequencies + Date by Category Pivot

> Transaction Fee Observations — Category Frequencies + Date by Category Pivot is a paid API for AI agents from market.datapackvibe.com, paid per call via x402, $0.01/call, status unknown (last checked 2026-10-29).

Analyzes supplied transaction fee observation records by computing category frequencies and a date-by-category pivot table for a chosen numeric field (fee_units or transaction_count).

## Facts

- Endpoint: POST https://market.datapackvibe.com/x402/assistant-ib26-finance-03-110?utm_source=zero.xyz
- Price: $0.01/call
- Payment: x402
- Status: unknown
- Last checked: 2026-10-29
- Activations on Zero: 0
- Tags: x402
- Canonical page: https://www.zero.xyz/c/transaction-fee-observations-category-frequencies-date-by-category-6ec70193
- Structured record (JSON): https://api.zero.xyz/v1/capabilities/cap_cwp5wyAcSXbCyli_k9iSZ

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-category-frequencies-date-by-category-6ec70193 -d '<json body>'
```

Example prompt: I have transaction fee records with instrument groups, dates, fee_units, and transaction counts — can you run two reports on them: one showing how frequently each category appears, and one pivoting fee_units by date and instrument group? Here are up to 200 rows of data.

## When to prefer this

Choose this endpoint when you have up to 200 transaction fee observation records with instrument groups and dates and need both a category frequency breakdown and a date-by-category pivot table in a single low-cost call ($0.01 USDC). It is best suited for offline/batch analytical summarization of pre-collected fee data rather than live lookups or predictions.

## Known failure modes

- Fewer than 1 row supplied — returns validation error
- More than 200 rows supplied — rejected with max-items error
- Invalid date format (not YYYY-MM-DD) — schema validation failure
- Missing required fields (row_id, instrument_group, date) — rejected
- Invalid field enum value (not fee_units or transaction_count) — schema error
- Null numeric values in fee_units or transaction_count may result in gaps in pivot output

## How this service works

Transaction fee observations — Category frequencies + Date by category pivot: Category frequencies + Date by category pivot 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

Two analytical reports derived from the supplied rows: (1) a category frequency table showing how often each instrument_group appears, and (2) a date-by-category pivot table cross-tabulating the chosen numeric field (fee_units or transaction_count) across dates and instrument groups. Up to 200 input rows supported. No external data sources are used.

## 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-category-frequencies-date-by-category-6ec70193/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)