get_available_models

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

With no annotations, the description must disclose behavioral traits. It states that the tool 'discovers' and 'recommends', implying a read-only operation, but does not explicitly confirm it is non-destructive or describe side effects. It also does not clarify the output format (e.g., a single recommendation vs. a list) or how the 'best' model is determined beyond the reading/writing criteria. This is a moderate gap.

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 two concise sentences, front-loaded with the primary action ('Discovers active models') and then the secondary purpose. There is no wasted verbiage, and the key information is presented efficiently.

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?

While the tool is simple (one optional parameter, no output schema), the description does not explain what the tool returns or how the agent should use the recommendation. It gives context about the intended use (reading and writing) but omits details about the response structure, which could leave an agent uncertain about the next steps. Given the lack of output schema, the description should carry more of this burden.

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 coverage is 100%, so the 'provider' parameter is already fully described in the schema, including the list of valid providers and the default behavior. The description does not add additional parameter-level meaning beyond what the schema provides, so the baseline score of 3 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?

The description clearly states the tool's purpose: discovering active models and recommending the best one for reading and writing tasks. It distinguishes itself from sibling tools (bulk_read, code_write) by focusing on model selection rather than performing the read/write operations themselves. The verb 'Discovers' and resource 'active models' are specific and unambiguous.

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 this tool—when an agent needs to delegate to the best model—but it does not explicitly state when NOT to use it or mention alternatives. It provides clear context about its role in model selection but lacks explicit exclusions. Given the sibling tools are actions, the distinction is implicit rather than spelled out.

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