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

The description goes well beyond annotations by disclosing that the call is slow (up to a few minutes), outputs a draft rather than a launched survey, requires review before further steps, and is limited to 5 calls per hour. This is valuable behavioral context that annotations do not convey.

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?

Four dense sentences deliver scope, output state, expected duration, follow-up workflow, and a rate limit. Every sentence earns its place, and the most important information is front-loaded.

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 creating tool with no output schema, the description is complete: it explains what is created, what state it is in, how long it takes, what limits apply, and exactly which subsequent tools to use. An agent has enough context to invoke it and continue correctly.

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 coverage is 100%, so the baseline is 3. The description adds the meaningful qualifier that the input is 'ONE research question,' clarifying that a full survey is generated from a single prompt rather than multiple questions. It also notes the result lands in the active workspace, which gives situational meaning to the call.

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 and resource: 'Build a complete survey ... from ONE research question using AI.' It clearly distinguishes itself from siblings like create_survey, create_survey_from_template, and suggest_survey_topic by emphasizing AI generation, draft mode, and the complete survey scope.

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?

Provides a clear post-call workflow: 'Review with list_questions, then set_targeting → preview_survey → launch_survey.' It also gives practical constraints like slowness and rate limit. It does not explicitly state when to prefer manual creation or template-based alternatives, so it stops short of a 5.

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