compare_models

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

No annotations are provided, so the description must carry the full burden. It discloses parallel execution and side-by-side response format, but does not mention failure handling, error behavior, or any constraints (e.g., rate limits). This is adequate but not comprehensive.

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: a single purpose sentence followed by a well-formatted Args block. Each line earns its place, with no redundant information. The structure is clear and front-loaded.

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 tool with no output schema, the description only vaguely mentions 'side by side' without specifying the return format. It also does not cross-reference sibling tools for discovering hosts/models or mention potential errors. Given its simplicity, it covers the basics but leaves gaps in return structure and operational context.

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 schema has 0% description coverage, and the description compensates well by explaining 'prompt' clearly and defining the 'targets' structure with an example. It adds meaningful semantics beyond the minimal schema types, though it could be more exhaustive about possible target keys.

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 a specific action: send the same prompt to multiple host/model pairs in parallel and return responses side by side. It distinguishes from sibling tools like generate (single model) and list_models (listing), focusing on parallel comparison.

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 the use case (comparing multiple models) and the parallel execution model, providing clear context. However, it does not explicitly state when not to use this tool or mention alternative tools, so it falls short of a 5.

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