academy_quiz

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 mentions the tool fetches quizzes but lacks details on permissions, rate limits, error handling, or what the fetched data includes (e.g., quiz questions, answers). For a read operation with zero annotation coverage, this leaves significant gaps in understanding its behavior.

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 front-loaded with the core purpose and efficiently lists parameter usage options in a single, well-structured sentence. Every part contributes directly to understanding how to invoke the tool, with no wasted words or 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 the tool's moderate complexity (4 parameters, no output schema, no annotations), the description is adequate but incomplete. It covers parameter usage well but lacks behavioral details like response format, error cases, or dependencies on other tools. Without annotations or an output schema, more context on what 'fetch' entails would improve completeness.

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 low at 25%, with only 'slug' and 'locale' having descriptions. The description compensates by explaining the semantic meaning of parameter combinations: 'slug' for direct access, 'level+lessonSlug' for lesson quizzes, and 'level' alone for checkpoints. This adds valuable context beyond the sparse schema, though it doesn't detail 'lessonSlug' or 'level' ranges beyond the schema's numeric constraints.

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 action ('Fetch a quiz') and specifies the resource types ('lesson quiz or end-of-level checkpoint'), making the purpose evident. However, it doesn't explicitly differentiate this tool from sibling tools like 'academy_quiz_submit' or 'academy_lesson', which might handle related but distinct operations, preventing a perfect score.

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 clear context on when to use specific parameter combinations (e.g., 'slug' alone, 'level+lessonSlug' for lesson quizzes, or 'level' alone for checkpoints), offering practical guidance. However, it doesn't mention when not to use this tool or explicitly compare it to alternatives like 'academy_lesson' or 'academy_quiz_submit', which could help avoid misuse.

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