replicate_get_model

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

The description implies a read operation but does not disclose any behavioral traits beyond that. With no annotations, the description should cover authentication, rate limits, or data freshness, but it does not.

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 a single sentence that is concise and front-loaded. However, it could be slightly more structured without losing brevity.

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?

Given the lack of output schema, the description does not explain what the return value contains (e.g., model details and version). It is too minimal to be fully complete for a tool with 3 required parameters.

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 description adds no parameter-level information beyond what is in the schema (only the 'owner' parameter has a description in the schema). Since schema coverage is low (33%), the description should compensate but fails to explain 'api_token' or 'model_name'.

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 (Get) and resource (Replicate model details and latest version). It distinguishes from the sibling `replicate_list_models` by focusing on a single model, though it does not explicitly contrast.

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?

No guidance on when to use this tool versus alternatives like `replicate_list_models` or `replicate_get_prediction`. No prerequisites, context, or exclusions are mentioned.

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