generate_quiz

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

No annotations are provided, so the description carries the full behavioral burden, yet it discloses nothing about generation time, whether the call is synchronous or queued, cost/quota implications, or where the resulting quiz is stored. It does not even clarify that this is a non-destructive generation call versus a mutation of notebook data.

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?

A single short sentence with no filler or repetition, so nothing is wasted. However, the brevity reflects under-specification rather than discipline; there is no front-loaded scope, output expectation, or parameter note.

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 annotations, no output schema, 0% parameter documentation, and an artifact-generating tool whose behavior (async, language defaults, source dependence) matters, the description is far too thin. An agent cannot invoke this correctly without guessing at the meaning of instructions and the timing of the result.

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% for two parameters, and the description adds no meaning for either: it never mentions notebook_id, which notebook the quiz targets, or that instructions can steer quiz content and language. With no compensating text for undocumented parameters, this is a clear gap.

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 and resource ('Gera um teste (quiz) no NotebookLM'), so an agent knows it produces a quiz artifact inside a notebook. It does not distinguish itself from near-siblings such as generate_flashcards or generate_summary_report, which are equally plausible for the same notebook, and it is written in Portuguese while the rest of the toolset is English.

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?

There is no indication of when to choose a quiz over flashcards, a summary report, or a data table, nor any prerequisite such as requiring sources to have been added first. The agent is left to infer usage entirely from the verb.

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