togetherai_list_models

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

Annotations already declare readOnlyHint, idempotentHint, openWorldHint and destructiveHint=false, so the safety profile is fully covered elsewhere. The description's only added value is the note that the result spans multiple model categories, which is mildly useful, but nothing is said about pagination, result size, or whether the catalog is live or cached.

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?

One sentence, front-loaded with the verb and resource, with the model-category enumeration as a compact qualifier. No filler, no restatement of the tool name.

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 one-parameter read tool with no output schema, the description leaves the agent guessing about what a returned model entry looks like (ID, context length, pricing) and whether the list is filtered by the key's entitlements. Adequate but thin given nothing else describes the response.

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?

There is a single parameter, api_key, and the schema already describes it at 100% coverage. The description says nothing about the API key, so it neither adds nor detracts from the schema — the baseline 3 applies.

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?

States a specific verb-and-resource pair ('List all available models on Together AI') and enumerates what the inventory covers (chat, completion, embedding, image). That is enough to separate it from siblings like togetherai_chat_completion, though the distinction from other provider list-models tools rests on the name alone.

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 use case (discovering which model IDs exist before calling a generation endpoint) is implied but never stated, and there is no explicit when-not or alternative guidance. No mention of the sibling togetherai_chat_completion / togetherai_create_embedding flow it presumably feeds into.

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