get_model_params

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

With no annotations, the description carries the full burden. It explicitly indicates the operation is a retrieval ('Get') and mentions a dependency ('Requires connection to the full Creative Claw MCP server'). It does not mention permissions or side effects, but for a read-only getter this is acceptable and non-contradictory.

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 composed of four sentences, but each sentence adds value: the first defines the action and resource, the second lists the return details, the third explains the benefit, and the fourth notes a prerequisite. It is slightly longer than necessary but remains focused and free of fluff.

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?

The description provides enough context for an agent to decide when to invoke it: it specifies the input (a specific model), the output (detailed parameters and tips), and the necessity for a connection. It lacks explicit error handling or fallback behavior, but this is not critical for a simple getter operation.

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 covers 100% of the parameter's meaning with a detailed description that includes examples. The tool description adds no additional information about the parameter beyond reinforcing that it refers to a specific model, 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 verb 'Get' and the resource 'detailed parameters, prompting guidelines, and technical specifications for a specific AI model.' It also enumerates the returned information (dimensions, duration ranges, cost, tips), making the purpose unambiguous and distinct from the sibling list_models tool.

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 by asserting it is 'Essential for optimizing generation quality and understanding model-specific features.' It implies that this is for retrieving details of a specific model rather than listing models, though it does not explicitly name the alternative tool.

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