model_set_current

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

With no annotations provided, the description must convey behavioral traits like side effects, state changes, and error conditions. It only states that it sets the current active model and returns a confirmation/error message, but fails to disclose what 'current active model' implies (e.g., it changes global state for subsequent operations) or how it behaves with invalid input.

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 concise with an efficient main sentence and additional structured sections (Args, Returns). It is front-loaded and avoids unnecessary detail, making it easy to scan.

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 simple one-parameter tool with no output schema or annotations, the description covers the basic purpose and parameter. However, it omits important context like error handling, prerequisites (model must exist), and post-condition behavior, making it minimally viable but not robust.

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 input schema has 0% coverage (no descriptions for parameters), so the description shoulders the burden of explaining the parameter. It adds 'Name of the model to set as current' which is basic but helpful. However, it does not clarify the expected format (e.g., model name vs. ID, path, or handle), leaving ambiguity.

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 action (set) and the target (current active model), indicating its role in selecting which model to use for subsequent operations. However, it does not explicitly differentiate from sibling tools like model_load or model_create, leaving the agent to infer that this tool is for switching between already-loaded models.

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 provides no guidance on when to use this tool versus alternatives, what prerequisites are needed (e.g., model must already be loaded), or what context it should be used in. The agent is left to guess the proper usage scenario.

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