fabric_create_quiz

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 only states the general action and does not reveal important traits such as the output format (e.g., multiple-choice questions), whether it invokes an external pattern, any limitations on input size, or how the questions are generated. This lack of transparency could leave an agent uncertain about side effects and expected results.

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 a single, efficient sentence that immediately states the tool's function. It is front-loaded with the key action and object, and contains no filler or redundant information.

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?

The tool is relatively simple with one parameter and no output schema, so the description should clarify what the generated quiz questions look like or any usage prerequisites. It does not mention output format, question types, or additional settings, leaving gaps in context for an agent. However, the basic purpose is clear enough for basic selection, hence a middle score.

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% as the only parameter 'input' is described as 'The input text to process'. The description adds minor semantic alignment by referring to 'content', but it does not elaborate on required structure, formatting, or examples beyond the schema. Since the schema already provides adequate meaning, a 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 clearly states the tool's purpose with a specific verb and resource: 'Generate quiz questions from content for learning'. It distinguishes itself from sibling tools like fabric_to_flashcards by focusing on quiz questions rather than flashcards, and from other content-processing tools by the explicit output type.

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 guidance on when to use this tool versus alternatives. The description merely states what it does, but never mentions scenarios, exclusions, or comparisons to similar tools like fabric_to_flashcards or fabric_analyze_claims. Without explicit usage context, an agent may misuse it.

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