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

The description goes far beyond the readOnlynHint annotation by disclosing important behavioral traits: the response deliberately omits answer indices and explanations to avoid leaking answers, out-of-range count values are refused rather than clamped, same seed yields reproducible results, and the question format follows digital-SAT vocabulary testing. This gives the agent strong expectations about what the tool will and will not return.

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 longer than minimal, but every section earns its place: purpose, use cases, critical no-answer caveat, parameter summary, and format note. Some parameter details repeat the schema, but they are compact and useful for an agent that may not open the schema. It is well-structured and front-loaded.

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 carries the burden of explaining the response shape. It does so well: no answer index, no explanations, each item is a sentence with one blanked word and four options, and items have ids used with check_answer. For a read-only, deterministic draw tool, this is complete enough for correct selection and 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%, so the baseline is 3. The description largely restates what the schema already documents: count range/default, difficulty levels, theme values, and seed behavior. It adds no significant new parameter semantics beyond what is already in the schema; the refusal behavior for count is also already in the schema.

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 opens with a specific verb+resource: it draws words-in-context vocabulary practice questions from a curated, human-written bank. It also differentiates itself from siblings like generate_items by emphasizing that it is free, deterministic, and costs no inference, so an agent can tell it apart.

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?

It explicitly lists use cases: quiz a learner, build a practice set, or inspect what a question looks like. It also tells the agent to call check_answer for answers, which helps route the workflow correctly. It does not explicitly name generate_items as the alternative for generative/non-deterministic draws, so it stops short of a full when-to-use-when-not-to-use guide.

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