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

The description adds useful behavioral context: it performs server-side template entitlement checks and never calls third-party models. However, readOnlyHint is false, implying possible state changes, and the description does not disclose what 'prepare' actually creates, saves, or modifies. The no-external-call guarantee is valuable, but the side-effect profile remains under-specified.

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?

Two sentences, front-loaded with the core purpose and followed by the most important behavioral caveat. No filler and no redundant repetition of schema information.

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 tool has 7 parameters, no parameter descriptions in the schema, and a similarly named sibling. The description does not explain how to construct a valid call, what the language or value fields do, or what the output represents. The existence of an output schema softens the return-value gap, but for this parameterized tool the description leaves too much unspecified.

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 0%, so the description must compensate for undocumented parameters, but it only maps 'canonical prompt' to prompt and 'two or more AI providers' to providers. The meaning of values, uiLanguage, inputLanguage, outputLanguage, and name is left entirely to inference from property names, which is insufficient at this coverage level.

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 names a specific verb ('prepare'), a clear resource ('one canonical prompt for two or more AI providers'), and the intended outcome ('compare answers'). It also distinguishes itself from build_prompt by referencing the same entitlement checks and explicitly stating it never calls third-party models. However, it does not explicitly differentiate from the near-identical sibling prepare_custom_compare, so it stops short of full sibling separation.

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 the tool is for multi-provider answer comparison and clarifies it does not call third-party models, which gives some usage context. But it does not state when to choose this tool over build_prompt or prepare_custom_compare, nor does it give exclusions or prerequisites beyond the entitlement-check mention.

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