Get Generation Model

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false. The description adds useful behavioral context by listing exactly what is returned (target LLM config, tags, creation time, warnings) and explains what warnings may indicate (deprecation). No contradiction with annotations.

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 and well-structured: an opening summary, a sentence on return values, and the Args breakdown. Every sentence provides necessary detail with no redundancy or filler.

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 read operation with one parameter and an output schema, the description is complete. It covers the purpose, return content, and parameter semantics. No additional context is needed for correct invocation.

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 provides only a parameter name with no description (0% coverage). The description's Args section explicitly states 'name: Name of the registered generation model,' fully compensating for the schema's lack of detail. This adds clear meaning beyond the bare type.

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 action ('Read detailed information about a registered generation model') with a specific verb and resource. It distinguishes from sibling tools like list_generation_models by emphasizing detailed single-item retrieval.

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 clear context for when to use the tool (to read details of an existing generation model), but it does not explicitly mention alternatives or exclusion criteria. It does not say 'use list_generation_models to list all models' which would make it a 5.

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