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

Annotations already declare readOnlyHint=true and openWorldHint=false, so safety is covered. The description adds genuinely non-obvious behavior: free-text answers and first names are only returned when the teacher has permitted Claude access to child data, which directly affects whether an agent can expect those fields. It does not mention pagination or result size limits, keeping it short of a 5.

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?

Three sentences, no filler, and the output content is front-loaded before the filtering and privacy caveats. Dense but every clause carries information; a slightly clearer lead-in naming the survey id would improve scanability.

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?

There is no output schema, so the description carries the burden of describing return values, and it does so concretely (counts, percentages, averages, skipped-by-condition counts). Combined with the privacy gating note and the filter pairing, an agent has everything needed to call this 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 67% and the description compensates by explaining the coupling of filter_question and filter_value (a pair that only makes sense together, and that filter_value accepts an answer id, yes/no, or a scale step). The required id parameter is never described in either place, but its meaning is evident from the tool name, so the gap is minor.

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?

States a specific operation on a specific resource and enumerates the actual outputs (count per question, percentage per answer, average for scales/numbers, count of participants who never saw the question due to a condition). That is far more than a restatement of the name. It does not explicitly contrast itself with get_survey or list_surveys, so an agent must infer the split from the names alone.

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 second sentence does give a concrete usage pattern: combine filter_question with filter_value to restrict results to respondents who answered a certain way. However, there is no statement of when to reach for this tool versus get_survey (definition) or list_surveys (discovery), and no prerequisites such as survey ownership or closed-state requirements.

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