list_llms

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

Annotations already indicate read-only, idempotent, open-world, and non-destructive behavior. The description adds value by specifying the fields returned (provider, model type, connection info), which helps the agent understand output. No disclosure of pagination behavior or total count, but sufficient given annotations.

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, concise and front-loaded with purpose. Each sentence adds essential context without redundancy. Ideal length.

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?

The tool has 5 parameters, no output schema, but good annotations. The description mentions the output fields, which partially compensates for no output schema. However, it does not explicitly mention pagination or list return structure. Overall adequate for the tool's simplicity.

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 description coverage is 100%, so baseline is 3. The description does not add any additional information about parameters beyond what is already in the schema. No parameter usage examples or clarifications are provided.

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 lists LLM configurations, explaining what LLMs are used for and what info is shown (provider, model type, connection info). This distinguishes it from sibling list tools by domain and purpose.

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 implies when to use (to list LLMs) but provides no explicit guidance on when not to use or alternatives. No direct comparisons to other tools like search_resources or get_llm are made. The filtering parameters in the schema offer implicit guidance, but description lacks usage context.

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