get_conversations

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 adds some context: it mentions the return format ('list of conversations with participants and last message preview') and includes a WARNING about using an unofficial API and bot detection risks. However, it lacks details on permissions, rate limits, pagination, or error handling, which are important for a read operation.

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 appropriately sized and front-loaded, starting with the core purpose. The Args and Returns sections are clear, and the WARNING is placed effectively. It could be slightly more concise by integrating the Args into the main text, but overall, it's efficient with minimal waste.

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?

Given the tool's moderate complexity (a read operation with one parameter), the description is fairly complete. It explains the purpose, parameter, return value, and includes a risk warning. With an output schema present, it doesn't need to detail return values further. However, it lacks usage guidelines and some behavioral details like error cases.

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 description adds meaningful semantics for the single parameter 'limit', explaining it as 'Maximum conversations to return (default: 20)'. Since schema description coverage is 0% and there's only one parameter, this compensates well. However, it doesn't specify constraints like minimum/maximum values or if it's optional (implied by default).

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 clearly states the tool's purpose: 'Get your LinkedIn messaging conversations.' It specifies the verb ('Get') and resource ('LinkedIn messaging conversations'), making it easy to understand what the tool does. However, it doesn't explicitly differentiate from sibling tools like 'get_conversation' or 'get_conversation_details', which prevents a perfect score.

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 no guidance on when to use this tool versus alternatives. It doesn't mention sibling tools like 'get_conversation' (singular) or 'get_conversation_details', nor does it explain prerequisites or contexts for usage. The WARNING about the unofficial API is a caution but not a usage guideline.

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