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

Annotations already provide readOnlyHint, openWorldHint, idempotentHint, and destructiveHint. The description adds meaningful behavioral detail: it separates answer/facts from citations, reports unconfirmed matters, and includes revision verification status. This reveals output structure and caveats that annotations do not express. No contradiction exists.

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, dense sentence that front-loads the purpose and then specifies the key output components. Every clause adds information: evidence basis, answer/facts separation, unconfirmed items, and revision verification status. No redundancy or filler.

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?

Given the lack of an output schema, the description does a good job of summarizing the return composition, but it remains high-level. It omits details about how the brief is structured, what filters like 'live' affect in terms of output confidence, and how this relates to sibling policy tools. Still, the core behavior is sufficiently conveyed for an agent to select and invoke the tool.

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%, so the baseline is 3. The description does not add parameter-specific guidance beyond echoing the 'query' concept ('학사 질문'). It does not explain nuance around 'live', 'limit', or 'category', but the schema fully covers those parameters.

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 uses a specific verb and resource: it returns an evidence-based academic policy brief with answer/facts and citations, including unconfirmed items and revision verification status. This clearly goes beyond the tool name. However, it does not explicitly differentiate itself from sibling search_academic_policy_sources or list_academic_policy_sources beyond implying synthesis.

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 '학사 질문에 대해' implies the tool is for academic policy questions that need evidence-backed answers. Yet there is no explicit when-to-use vs alternatives guidance, such as when to choose this over check_graduation_requirements, evaluate_graduation_with_policy, or search_academic_policy_sources. Usage context is inferable but not stated.

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