get_models

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

Annotations already declare readOnlyHint=true, idempotentHint=true, openWorldHint=true and destructiveHint=false, so the safety profile is covered. The description adds nothing beyond those structured fields — no scope, no result shape, no rate-limit or auth context.

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?

Two words is not conciseness but under-specification; the text is too short to earn its place as a description. There is no front-loaded information beyond the title itself.

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 parameterless read tool with no output schema, the description still needs to disambiguate the resource, and it does not. With many 'get/list' siblings in the catalog, an agent cannot determine what this returns or when to prefer it.

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 tool takes zero parameters and schema description coverage is 100%, so there is nothing for the description to clarify. Per the baseline for parameterless tools, a 4 is appropriate.

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?

"Get Models" restates the tool name/title with no added specificity: it does not say what kind of models (LLM models, speech models, fine-tuned models), what scope, or what is returned. In a sibling list containing list_available_llms, get_speech_engine, get_finetunes and get_tools_route, the agent cannot tell which resource 'models' refers to.

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?

There is no usage guidance of any kind — no when-to-use, no when-not-to-use, and no mention of any alternative sibling. The agent is left to guess entirely.

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