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hotmart_sales_price_details_list

Retrieve sales price details filtered by transaction status, product, date range, or other criteria to analyze pricing and transaction data.

Instructions

Sales Price Details. Example: hotmart_sales_price_details_list(transaction_status='APPROVED').

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
transactionNoTransaction code
transaction_statusNoTransaction status.
max_resultsNoMax results per page
page_tokenNoPagination token for the next page
product_idNoProduct ID
start_dateNoStart date. Unix timestamp in **milliseconds** (not seconds, not ISO). Ex: `1730419200000` = 2024-11-01 00:00 UTC. Python: `int(datetime(2024,11,1).timestamp() * 1000)`.
end_dateNoEnd date. Unix timestamp in **milliseconds** (not seconds, not ISO). Ex: `1730419200000` = 2024-11-01 00:00 UTC. Python: `int(datetime(2024,11,1).timestamp() * 1000)`.
payment_typeNoPayment type.
selectNoCustom field selection in response

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior2/5

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

No annotations provided, and the description fails to disclose behavioral traits such as read-only nature, pagination, or rate limits. The example only shows a single use case.

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?

The description is very short (one line plus an example), which is concise but lacks detail. It could be expanded without being verbose.

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 and a likely complex output (though output schema exists), the description provides minimal context. It does not explain pagination, return values, or typical use cases.

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 coverage is 100% with clear descriptions for each parameter (e.g., start_date explains Unix timestamp in milliseconds). The description adds no extra meaning, but the schema itself is adequate.

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

Purpose2/5

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

The description 'Sales Price Details' is vague and does not specify the action (list, get, etc.) or distinguish from sibling tools like commissions or breakdown. The example adds context but not clarity.

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 vs. other sales-related tools. The example implies filtering by transaction_status but does not explain when not to use it.

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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