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

The description adds meaningful behavioral context beyond the annotations: it returns explanations for every option, and it warns that multiple options are often defensible but only one is credited, which shapes the user's expectations. The annotations do not claim read-only behavior, so nothing here contradicts them.

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 sentences, no filler. The main function and distinctive behavior are front-loaded, and the second sentence adds valuable exam-specific context that helps the agent understand why the tool behaves as it does. Every sentence earns its place.

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?

With no output schema, the description reasonably explains what the tool returns (an explanation for every option) and signals the correctness-grading nature. It could specify the output format or whether the answer is recorded, but for its simplicity the description is sufficiently complete for correct invocation.

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%, and the input schema already documents each parameter clearly, including the expected format for 'selected'. The description does not add parameter-specific semantics, but the schema carries the burden adequately, so the baseline 3 applies.

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 names a specific verb ('Grades') and resource ('the user's choice'), and explicitly states the distinctive behavior: returning an explanation for every option. This clearly differentiates it from sibling tools like get_practice_question, which fetches questions rather than evaluating answers.

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 description implies the tool is used after the user has selected an answer on an exam question, and the exam-context sentence explains why the wrong-option explanations matter. However, it does not explicitly state when to use it versus alternatives, nor does it mention prerequisites such as first obtaining a question_id from get_practice_question.

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