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

Beyond the readOnlyHint annotation, the description discloses the full return content: correctness, the right option, why it fits, why the chosen option was wrong, and why every distractor fails. It also adds a crucial behavioral expectation — read distractor reasons aloud even on correct answers — which materially changes how an agent should use the result.

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 but information-dense: it opens with the core purpose, enumerates the returned content, includes a directly actionable pedagogical instruction, and ends with input requirements. Every sentence earns its place, and the most important operational detail about reading distractor reasons is highlighted.

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 fully carries the burden of explaining return values, and it does so explicitly. It also covers the input source and gives behavioral guidance, making the tool safely and correctly invocable without needing to infer missing details.

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 schema already documents both id and choice. The description restates the same information ('id from a draw response', 'zero-based index') without adding new meaning, earning the baseline score.

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 'Check' with a clear resource ('an answer to a practice item') and states the output ('get the teaching content'). It is immediately distinguishable from sibling tools draw_items and generate_items, which create or retrieve items rather than evaluate 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 clearly implies the workflow by stating that the id comes from a draw response, so the agent knows this tool is used after draw_items. It does not explicitly name alternatives or state when not to use this tool, but the workflow context is strong enough to guide correct selection.

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