get_conversations

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

The description only states the action without disclosing behavioral traits like what data is returned, pagination behavior, or any side effects. Since no annotations are provided, the description carries the full burden for transparency, which it fails to meet. The tool is a read operation, but this is not explicitly stated.

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 a single, concise sentence with no unnecessary words. It is front-loaded with the essential verb and resource. While lean, it earns its place by being direct, though it could be slightly expanded for completeness.

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 simple retrieval tool with only two optional parameters and no output schema, the description is minimally adequate. It covers the core purpose but omits context like default behavior of the filter parameter or whether the results are ordered. Overall, it meets the minimum viable bar.

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?

Schema coverage is 100%, so the description does not need to add much. It lists the parameter names implicitly, but does not provide additional context beyond what the schema already offers. The baseline of 3 is appropriate as the schema does the heavy lifting.

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 verb 'Get' and the resource 'LinkedIn conversations from Waalaxy inbox', making the purpose immediately understandable. However, it does not distinguish this tool from siblings like get_prospects or get_campaigns, which also fetch list-type data.

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?

No guidance is provided on when to use this tool versus alternatives. The description lacks any indication of prerequisites, context, or exclusions. Without such guidance, an AI agent may not know if this is the appropriate tool for tasks involving specific conversation subsets.

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