generate_mcq

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only states the basic action of generating MCQs without any details about how it works (e.g., source of information, quality of questions, potential rate limits, or authentication needs). For a tool with no annotations, this is a significant gap in transparency, as it doesn't reveal important behavioral traits beyond the surface-level purpose.

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 extremely concise and front-loaded, consisting of a single sentence that directly states the tool's purpose. There's no wasted language or unnecessary details, making it easy to parse quickly. Every word earns its place by conveying essential information without redundancy.

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?

Given that there's an output schema (which likely defines the structure of generated MCQs), the description doesn't need to explain return values. However, with no annotations, 0% schema description coverage, and a sibling tool, the description is incomplete. It covers the basic purpose but lacks details on usage, behavior, and parameters, making it only minimally adequate for the tool's complexity.

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?

The description mentions 'about a given topic,' which hints at the 'topic' parameter, but it doesn't cover the other parameters ('difficulty' and 'num') or provide any additional meaning beyond what the input schema already defines. With 0% schema description coverage, the description adds minimal value, but since there's only one parameter count (a nested object 'request'), the baseline is adjusted. However, it doesn't fully compensate for the lack of schema descriptions, warranting a score of 3.

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: 'generate Multiple Choice Questions (mcqs) about a given topic.' It specifies the verb (generate) and resource (MCQs), making it easy to understand what the tool does. However, it doesn't explicitly differentiate from its sibling tool 'generate_flashcard' (which might generate different educational content), so it doesn't reach the highest score of 5.

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 provides no guidance on when to use this tool versus alternatives. It doesn't mention the sibling tool 'generate_flashcard' or any other context for choosing between them. There's no information about prerequisites, limitations, or specific scenarios where this tool is preferred, leaving the agent with minimal usage context.

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