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

The annotations already signal read-only and open-world behavior. The description adds valuable behavioral context beyond annotations: the teaching content returned, the explicit instruction to read distractor reasons even when the learner is correct, and the source/ownership of the question bank. This is more than the annotations alone provide.

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 front-loaded with the core purpose and then organized into helpful sections. The 'WHY DELEGATE THIS' and direct-call sections are extra content, but they earn their place by clarifying when and why to use this tool. Slightly longer than the minimum, but every sentence adds decision-relevant value.

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?

There is no output schema, so the description takes on the burden of explaining return content, and it does so thoroughly: right/wrong, correct option, explanation of fit, and explanations for every distractor. Combined with the two fully documented parameters, the agent has enough to select and invoke the tool correctly without ambiguity.

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%: the id is described as 'Item id from a draw response' and choice as 'Zero-based index of the chosen option.' The description adds no further parameter semantics, so the baseline of 3 is appropriate.

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-resource pairing: 'Mark an attempt and get the teaching content' and enumerates exactly what is returned: correctness, correct option, why it fits, and why every distractor fails. This clearly distinguishes it from sibling tools like vocab_draw, which would draw the question rather than check an answer.

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 clear context for when to use the tool: after a learner has selected an option. The 'WHY DELEGATE THIS' section explains the rationale for using the curated bank over generated questions, and the note about calling the service directly offers a clear alternative. It does not explicitly say 'use vocab_draw to obtain the id first,' but the schema's 'Item id from a draw response' covers that connection.

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