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

Annotations already declare this is a non-read-only, open-world, non-destructive operation. The description adds useful behavioral context: it generates exactly 5 questions and includes multiple alternative answers per question. However, it does not explain persistence (where the quiz is stored), whether course_id affects unit completion tracking, or what the response looks like, leaving meaningful behavioral gaps for a creation tool.

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 three sentences, front-loaded with the core capability, then mode distinctions, then output detail. Every sentence contributes useful information without redundancy, despite the long source list being schema-redundant.

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?

For a complex, 13-parameter creation tool with no output schema, the description covers the main modes and question structure. However, it omits important context such as where generated quizzes are saved, whether the tool returns quiz IDs or question objects, and how course_id tracking interacts with generation. The rich schema mitigates this, but some agent-critical context is still missing.

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 coverage is 100%, so parameter-level details are already handled by the schema. The description still adds value by grouping parameters into two mutually exclusive modes (unit_id vs. title plus sources) and clarifying that title is required for standalone generation. This mode grouping helps an agent navigate the 13 optional parameters beyond individual schema descriptions.

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: 'Generate 5 AI-powered fill-in-the-blank questions.' It also distinguishes the two creation pathways (unit_id vs. custom sources) and notes that each question has alternative answers, which separates it from sibling tools like create_mcq or create_quiz.

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 clearly explains the two usage modes: course-based via unit_id and standalone via title plus sources. It does not explicitly compare itself to sibling creation tools (e.g., create_mcq, create_quiz) or state when not to use it, but the mode-selection guidance is strong and actionable.

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