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quiz_create

Create quizzes from NotebookLM content to test knowledge and reinforce learning. Specify sources, question count, and difficulty level for customized assessments.

Instructions

Generate quiz. Requires confirm=True after user approval.

Args: notebook_id: Notebook UUID source_ids: Source IDs (default: all) question_count: Number of questions (default: 2) difficulty: Difficulty level (default: 2) confirm: Must be True after user approval

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
notebook_idYes
source_idsNo
question_countNo
difficultyNo
confirmNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions the confirm requirement, which implies a safety mechanism, but doesn't describe other behavioral traits like what happens during quiz generation, error conditions, or rate limits. The description adds some context but lacks comprehensive behavioral details.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness3/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is appropriately sized but not optimally structured. The first sentence is front-loaded with key information, but the Args section uses inconsistent formatting (e.g., mixing descriptions with default values). It could be more streamlined, though all content is relevant.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's complexity (5 parameters, no annotations, but has output schema), the description is fairly complete. It covers all parameters with semantics and includes a usage guideline. Since an output schema exists, it doesn't need to explain return values, making this adequate for the context.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

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 provides meaningful semantics for all 5 parameters: notebook_id as 'Notebook UUID', source_ids as 'Source IDs (default: all)', question_count as 'Number of questions (default: 2)', difficulty as 'Difficulty level (default: 2)', and confirm as 'Must be True after user approval'. This adds significant value beyond the bare schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose with the verb 'Generate' and resource 'quiz', making it specific and actionable. It distinguishes itself from sibling tools like 'flashcards_create' or 'report_create' by focusing on quiz generation. However, it doesn't explicitly differentiate from all potential alternatives in the sibling list.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides clear context for usage with the requirement 'Requires confirm=True after user approval', indicating when the tool should be invoked. It doesn't explicitly mention when not to use it or name specific alternatives among siblings, but the user approval requirement gives practical guidance.

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

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