affiliate_hotmart_list_transactions

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It does mention that the tool returns Transaction records including derived ageDays, which is useful return-format context. However, it does not disclose authentication requirements, pagination behavior, or what happens when no filters are provided, leaving gaps for a tool with no annotation-based safety profile.

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

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

The description is three sentences long, front-loaded with the primary purpose, followed by usage examples and return-info. Every sentence earns its place, and there is no redundancy or fluff. It is compact yet information-dense, ideal for an agent to quickly parse.

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

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

For a tool with 9 parameters, no output schema, and no annotations, the description is reasonably complete. It covers the core functionality, common use cases, and points to a sibling tool for aggregate totals. It does not address pagination or default date-window behavior, which would be useful, but the description still gives the agent enough context to select and invoke the tool correctly in most scenarios.

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

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

The schema has zero description coverage, so the description must compensate. It adds meaning for several parameters: 'within a window' maps to from/to, 'specific programme' maps to programmeId, and the listed statuses (earned, pending, reversed, paid) map to the status parameter. It also hints at ageDays, which relates to minAgeDays/maxAgeDays. However, it does not explain limit, cursor, or offset, which remain ambiguous despite their self-explanatory names.

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

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

The description uses a specific verb ('List') and resource ('affiliate transactions' on Hotmart), and immediately clarifies the scope: within a window or for a specific programme. It also distinguishes itself from sibling tools by listing the relevant statuses (earned, pending, reversed, paid) and explicitly pairing with get_earnings_summary for aggregate totals. This clearly differentiates it from other transaction-listing tools for different networks.

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

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

The description provides concrete example user queries ('what did I earn last month?', 'what's still pending?', 'show me reversed sales') that signal exactly when to use this tool. It also states that for aggregate totals, one should use get_earnings_summary instead, offering an explicit alternative. This gives the agent strong selection guidance without ambiguity.

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