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

Beyond the annotations (readOnlyHint, idempotentHint), the description adds valuable context: the tool is free and requires no payment, and it explicitly states that it is safe to call repeatedly. It also discloses the return format (JSON array with specific fields) and explains the isDefault flag behavior, which are not covered by 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, front-loading the purpose, then usage, return format, filtering, and safety in a logical flow. Each sentence adds necessary information with no fluff or redundancy, making it efficient for an agent to parse.

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 tool's simplicity (one optional parameter, no output schema), the description is comprehensive. It covers purpose, usage timing, filtering, return structure, default behavior, and safety attributes, leaving no obvious gaps for an agent to interpret the tool's behavior.

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 already fully describes the single optional 'category' parameter, including its enum and note that it matches tool names. The description's mention of filtering by category essentially reiterates what the schema provides, adding no new semantic meaning. Since schema coverage is 100%, the baseline is 3, and the description does not elevate it.

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 discovers available AI models with specific attributes like IDs, tier, capabilities, and pricing, and explicitly distinguishes its role from create_payment. The verb 'Discover' plus resource 'AI models' makes the purpose unambiguous, and the mention of numeric IDs and pricing differentiates it from related tools like get_model_pricing.

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 explicit usage guidance: 'Call this before create_payment to find the right modelId for your task.' It also explains filtering by category and notes that default models are used if modelId is omitted. This clearly tells when and how to use the tool, with direct reference to its role in a workflow.

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