infomaniak_list_ai_models

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

Annotations already provide readOnlyHint, idempotentHint, and openWorldHint. The description adds that it lists models, consistent with annotations. No additional behavioral details like pagination or rate limits are provided, but the annotations cover the safety profile sufficiently.

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 sentences, no fluff. First sentence states purpose with examples, second sentence gives usage context. Every sentence earns its place.

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?

Despite the tool's simplicity (zero parameters, output schema exists), the description provides sufficient context: lists model types, examples, and relevance to the chat endpoint. It is complete for the tool's scope.

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 no parameters, so the baseline is 4. The description does not need to add parameter information; it correctly describes what the tool does without referencing parameters.

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 'List', the resource 'public catalogue of LLM/STT/embedding models', and provides specific examples (Mixtral, Llama variants, Whisper). It effectively distinguishes from sibling tools like infomaniak_list_ai_products.

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 gives clear context by stating it is useful for targeting the OpenAI-compatible chat endpoint, implying when to use this tool. However, it does not explicitly state when not to use it or compare against alternatives like infomaniak_list_ai_products.

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