list_supported_models

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

Annotations are nonexistent, so the description carries the full burden of behavioral disclosure. It only says 'List', which implies read-only, but does not explicitly state safety, permissions, or side effects. The return type is the only behavioral clue.

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 short and front-loaded with the purpose. The 'Returns' line is somewhat redundant with the opening sentence, but the overall structure is clear and economically written.

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 tool with an output schema provided, the description captures the essential purpose and return. However, it could have briefly mentioned how this model list fits into the translation process, which is minor given the simplicity of the tool.

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 has zero parameters and the input schema confirms this. There is nothing for the description to add. The baseline for 0-parameter tools is 4, and the description correctly contains no parameter-specific text.

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 states a specific verb, 'List', and a clear resource, 'all supported Amazon Bedrock Mantle models for translation'. This clearly differentiates it from sibling tools like list_supported_languages or the translation/export operations.

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 guidance about when to use this tool, no mention of alternatives or exclusions, and no context about how this relates to the translation workflow. The agent must infer its usage externally.

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