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

Annotations already declare readOnlyHint=true and destructiveHint=false, indicating a safe read operation. The description adds useful context by specifying the return metrics (views, responses, completion rate), but does not disclose any caveats such as data freshness or permission requirements. This adds some value beyond the annotations without being rich.

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 concise sentence that front-loads the tool's purpose and key output. Every word earns its place, with no filler or 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 simple one-parameter tool with no output schema, the description adequately conveys what the tool returns. It lists the key metrics, but does not specify the exact response format or mention any limitations (e.g., 'only aggregate data, not raw responses'). Slight gap, but generally complete.

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 input schema provides 100% coverage: survey_id is described as 'The survey ID'. The description does not add extra meaning to the parameter. Since the schema carries the full burden, the baseline 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 states a specific verb ('get') and resource ('analytics summary for a survey'), and clearly lists the metrics it returns (views, responses, completion rate). This distinguishes it from sibling tools like get_survey or get_response, which focus on survey details or individual responses.

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?

Usage context is implied: if you need aggregate analytics, this is the tool. However, it does not explicitly name alternatives (e.g., for survey details use get_survey) or any exclusions. The sibling list is available, but the description itself provides no explicit when/when-not guidance.

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