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

No annotations are provided, so the description carries the full burden. It usefully discloses that the call is FREE, which is a meaningful behavioral trait, but it does not state read-only status, authentication requirements, rate limits, or return format.

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 short fragments front-load the action and then the audience/cost. Every word earns its place, with no redundancy or buried 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?

For a simple, zero-parameter read tool with no output schema, the description covers what it does and that it is free. However, it omits the natural next step (submitting answers via submit_survey) and does not explain the format of the returned questions.

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 tool has zero parameters, so there is nothing for the description to clarify beyond the empty schema. The baseline for zero-parameter tools is 4, and the description adds no confusing or contradictory parameter guidance.

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 (survey questions), and the added purpose 'for AI agents to provide feedback' distinguishes it from sibling tools like get_survey_stats and submit_survey. An agent can tell exactly what this tool returns without opening the schema.

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 phrase 'for AI agents to provide feedback' implies the intended use context (fetch questions before submitting feedback), but it never explicitly states when to call this versus submit_survey or get_survey_stats. Usage is only implied, not clearly instructed.

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