get_answer_key

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

With no annotations, the description carries the full behavioral burden. It does disclose the returned data form (question number → answer), but it does not mention read-only behavior, failure modes, missing answer keys, or any limitations. The '取' wording implies retrieval, but little else is transparent.

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 compact sentence with no filler or redundancy. It front-loads the core purpose and includes the useful output mapping in parentheses.

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 tool with three required parameters, no annotations, and no output schema, the description covers only the basic purpose and result shape. It omits parameter semantics, usage context, disambiguation from siblings, and error/edge-case behavior, so it is not complete enough for reliable agent 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 0%, so the description must compensate for the three undocumented parameters. It only refers to '某份試卷' without explaining how year, exam_code, and subject combine or what formats are expected. An agent would have to infer meaning purely from parameter names.

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 clearly states the action ('取' / get), the resource (standard answers for the test questions of a specific exam paper), and the output shape (question number → answer). This distinguishes it from sibling tools like get_model_answer, which suggests a different kind of answer output.

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 gives no guidance on when to use this tool versus related alternatives such as get_model_answer, get_exam_paper, or get_question. There are no exclusions, prerequisites, or context signals to help an agent choose it over siblings.

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