record_answer

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

No annotations are provided, so the description carries the burden. It discloses that the tool mutates state (records an answer, updates scheduling) and that it auto-grades MCQ, with optional self-grading for essays. It does not disclose side effects like whether progress is overwritten, whether scheduling changes are irreversible, or whether repeated calls for the same qid are idempotent.

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 compact and front-loaded with the main action, then adds a useful conditional detail about MCQ vs essay. Every sentence earns its place, though the second sentence could be slightly more explicit about parameter usage.

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 mutation tool with no annotations and no output schema, the description gives the core behavior but omits important context: what happens on repeated calls, whether grading is synchronous, and what the return value indicates. The sibling list shows many read-only tools, so the mutation nature is clear, but an agent might still need more detail to invoke it safely.

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. It explains self_correct's role for essay questions, which adds meaning beyond the schema. However, it does not explain the 'answer' parameter's format or how qid relates to question types, leaving some parameter semantics to inference.

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 ('記錄' record) and resource ('作答' answer), and clearly distinguishes itself from sibling tools by mentioning automatic grading and spaced-repetition scheduling. It also differentiates MCQ vs essay behavior, which helps an agent understand the tool's core function.

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 when to use this tool: when recording an answer that should be graded and scheduled. It does not explicitly state when not to use it or name alternatives, but the sibling list includes many read-only tools, so the mutation purpose is fairly clear. However, it lacks explicit guidance on when to use self_correct or how this relates to other practice tools.

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