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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is known. The description adds behavioral context beyond annotations: it enforces a 2-5 model range (not in schema) and indicates the tool returns a recommendation based on use case. It also lists the comparison dimensions, which clarifies expected behavior.

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, front-loaded sentence that efficiently conveys purpose, scope, and output. Every clause adds value, with no redundant information 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?

The description is complete for a read-only comparison tool with an output schema. It states the input range and criteria, the output type (comparison table with recommendation), and the use-case parameter. Since annotations cover safety and an output schema exists, no further details are necessary.

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?

Schema description coverage is 100%, so both 'models' and 'use_case' are already explained. The description adds value by specifying the 2-5 count constraint on 'models' and clarifying that 'use_case' optimizes the recommendation, which goes beyond the schema's enum descriptions.

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 function: 'Compare 2-5 AI models side by side' with specific attributes (context window, pricing, multimodal, reasoning, provider). It uses a specific verb and resource, and it distinguishes itself from siblings like 'compare_responses' (which likely compares outputs) and 'model_info' (single model info).

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 when to use the tool ('based on your use case') and lists the comparison criteria, providing clear context. However, it does not explicitly mention alternatives or exclusion conditions, such as when to use 'compare_responses' instead. No explicit 'when not to use' guidance is given.

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