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hotmart_sales_summary_list

Retrieve aggregated sales summaries filtered by transaction status, product, date, affiliate, and more for Hotmart sales.

Instructions

Sales Summary. Example: hotmart_sales_summary_list(transaction_status='APPROVED'). Don't use this for per-transaction details — use hotmart_sales_history_list for the raw list.

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)`.
sales_sourceNoSale source
affiliate_nameNoNome do afiliado
payment_typeNoPayment type.
offer_codeNoOffer code. Format: alphanumeric Hotmart code (ex: `H123A4B5`, not UUID, not int)
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 are provided, so the description must carry the full burden of behavioral disclosure. However, it only gives a bare example and does not explain whether the function is read-only, what aggregation occurs, or what the output structure looks like. For a tool named 'summary', the lack of detail about grouping or calculation is a significant gap.

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

Conciseness5/5

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

The description is two sentences with an inline example, no redundant information, and front-loaded with the key purpose. Every word earns its place.

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 12 parameters, an output schema exists but is not described, and no annotations, the description is far too minimal. It omits what a 'sales summary' entails (e.g., grouped totals, time periods), the meaning of the output, or how to use parameters like 'select'. The tool's complexity demands more context.

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 the baseline is 3. The description adds an example usage but no additional parameter semantics beyond what the schema already provides. The schema descriptions are adequate but not enriched by the tool description.

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

Purpose5/5

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

The description states 'Sales Summary' and provides an example with 'transaction_status='APPROVED'', which clearly indicates it returns aggregated sales data. It also explicitly distinguishes from 'hotmart_sales_history_list' for per-transaction details, so the purpose is specific and unambiguous.

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

Usage Guidelines5/5

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

The description explicitly says 'Don't use this for per-transaction details — use `hotmart_sales_history_list` for the raw list.' This provides clear when-to-use and when-not-to guidance, including naming the alternative sibling tool.

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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