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

Annotations declare readOnlyHint=true and destructiveHint=false, so the description doesn't need to repeat that this is a safe read operation. The description adds that it 'AI-picks' a category, implying a model-driven selection but not disclosing any additional behavior like whether it modifies anything (it doesn't per annotations) or whether it might return no result if no category fits. Given annotations cover the safety profile, a 3 is appropriate – the description adds minimal behavioral context beyond what annotations already provide.

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 one concise sentence that clearly states the tool's purpose and references the source of categories. It is front-loaded with the key action and resource, and there is no waste. It efficiently conveys the core information without redundancy.

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 tool with one parameter, full schema coverage, no output schema, and read-only annotations, the description is nearly complete. It tells the agent the source of valid categories and the purpose. It doesn't describe the return format, but since there is no output schema, the agent might need to infer the response; however, for a simple suggestion tool, the description is sufficient. It could mention that the output is a category string, but the tool name and description imply that. Overall, it's complete for the given complexity.

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%, meaning the schema already documents the 'research_question' parameter with its type and character range. The description adds that the question is used to 'AI-pick' a category, which gives purpose but not additional semantics about the expected format or how the question influences the selection. Since the schema fully describes the parameter, a baseline of 3 is correct; the description provides marginal extra meaning but not significant new insight.

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 states a specific verb ('AI-pick') and resource ('best topic category') and ties it to a source ('from get_survey_options.categories'). It distinguishes this from other survey-related tools, though it doesn't explicitly contrast with siblings. The phrase 'AI-pick' is clear but could be more direct about what the tool does (selects a category based on the research question).

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 used when you have a research question and want a topic category, and it references get_survey_options.categories as the source of valid options. It doesn't explicitly state when not to use it or name alternatives, but the context suggests it's a specialized suggestion tool distinct from listing categories. Usage guidance is adequate but not explicit.

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