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get_sales_commissions

Get sales commissions by applying filters like product ID, date range, transaction status, and commission role to refine results.

Instructions

Sales Commissions

Retorna as comissões de vendas.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
max_resultsNoNúmero máximo de resultados por página
page_tokenNoToken de paginação para a próxima página
product_idNoID do produto
start_dateNoData inicial (timestamp em milissegundos desde epoch)
end_dateNoData final (timestamp em milissegundos desde epoch)
transactionNoCódigo da transação
commission_asNoPapel de comissão do usuário autenticado. Values: PRODUCER, COPRODUCER, AFFILIATE
transaction_statusNoStatus da transação. Values: APPROVED, BLOCKED, CANCELLED, CHARGEBACK, COMPLETE, EXPIRED, NO_FUNDS, OVERDUE, PARTIALLY_REFUNDED, PRE_ORDER, PRINTED_BILLET, PROCESSING_TRANSACTION, PROTESTED, REFUNDED, STARTED, UNDER_ANALISYS, WAITING_PAYMENT
selectNoSeleção de campos customizados na resposta

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Implementation Reference

  • The `get_sales_commissions` async function that implements the tool logic. It calls the Hotmart API endpoint /payments/api/v1/sales/commissions with optional query params and returns JSON.
    async def get_sales_commissions(
        max_results: Optional[int] = None,
        page_token: Optional[str] = None,
        product_id: Optional[int] = None,
        start_date: Optional[int] = None,
        end_date: Optional[int] = None,
        transaction: Optional[str] = None,
        commission_as: Optional[str] = None,
        transaction_status: Optional[str] = None,
        select: Optional[str] = None,
    ) -> str:
        """Sales Commissions
        
        Retorna as comissões de vendas.
        
        Args:
            max_results: Número máximo de resultados por página
            page_token: Token de paginação para a próxima página
            product_id: ID do produto
            start_date: Data inicial (timestamp em milissegundos desde epoch)
            end_date: Data final (timestamp em milissegundos desde epoch)
            transaction: Código da transação
            commission_as: Papel de comissão do usuário autenticado. Values: PRODUCER, COPRODUCER, AFFILIATE
            transaction_status: Status da transação. Values: APPROVED, BLOCKED, CANCELLED, CHARGEBACK, COMPLETE, EXPIRED, NO_FUNDS, OVERDUE, PARTIALLY_REFUNDED, PRE_ORDER, PRINTED_BILLET, PROCESSING_TRANSACTION, PROTESTED, REFUNDED, STARTED, UNDER_ANALISYS, WAITING_PAYMENT
            select: Seleção de campos customizados na resposta"""
        endpoint = "/payments/api/v1/sales/commissions"
        params = {}
        if max_results is not None:
            params["max_results"] = max_results
        if page_token is not None:
            params["page_token"] = page_token
        if product_id is not None:
            params["product_id"] = product_id
        if start_date is not None:
            params["start_date"] = start_date
        if end_date is not None:
            params["end_date"] = end_date
        if transaction is not None:
            params["transaction"] = transaction
        if commission_as is not None:
            params["commission_as"] = commission_as
        if transaction_status is not None:
            params["transaction_status"] = transaction_status
        if select is not None:
            params["select"] = select
        result = await get_client().get(endpoint, params=params)
        return json.dumps(result, indent=2)
  • The function is exported via __all__ in the sales module, which is re-exported by tools/__init__.py and auto-discovered by the MCP server.
    __all__ = ["get_sales_history", "get_sales_summary", "get_sales_participants", "get_sales_commissions", "get_sales_price_details", "refund_sale"]
  • The server's `_discover_and_register_tools` function auto-discovers all async coroutine functions in the tools package and registers them with FastMCP as MCP tools.
    def _discover_and_register_tools() -> int:
        """Import all modules under hotmart_mcp.tools and register async functions."""
        registered = 0
    
        for module_info in pkgutil.iter_modules(tools_pkg.__path__, prefix=f"{tools_pkg.__name__}."):
            if module_info.name.endswith("__init__"):
                continue
    
            module = importlib.import_module(module_info.name)
    
            for name, obj in inspect.getmembers(module, iscoroutinefunction):
                if name.startswith("_"):
                    continue
                mcp.tool()(obj)
                registered += 1
    
        return registered
  • The tools __init__.py re-exports all functions from the sales module (among others), making get_sales_commissions discoverable by the server.
    """Auto-generated: re-exports all tool functions."""
    
    from .club import *  # noqa: F401,F403
    from .coupons import *  # noqa: F401,F403
    from .negotiation import *  # noqa: F401,F403
    from .products import *  # noqa: F401,F403
    from .sales import *  # noqa: F401,F403
    from .subscriptions import *  # noqa: F401,F403
    from .tickets import *  # noqa: F401,F403
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description must disclose behavior. It only says 'returns commissions' without mentioning read-only nature, pagination (despite page_token parameter), filtering capabilities, or side effects.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Extremely concise (two short sentences) but at the cost of missing critical usage details. Efficiency is good, but it's underspecified.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness2/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given 9 parameters, many siblings, and no annotations, the description is incomplete. It lacks usage guidance, behavior details, and context for parameter interdependencies.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so baseline is 3. Description adds no extra parameter context beyond what's in the schema, but schema is sufficient.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

Description states 'Retorna as comissões de vendas' (returns sales commissions), clearly indicating it retrieves commission data. This distinguishes it from sibling tools like get_sales_history or get_sales_summary, but lacks specifics on scope (e.g., authenticated user's commissions).

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

No guidance on when to use this tool versus alternatives. With many sibling tools (e.g., get_sales_history, get_sales_price_details), the description gives no context for selection.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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