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

Annotations already establish readOnly, idempotent and non-destructive, so 'Read-only' repeats structured data. The value-add is the honest scope limit: the check covers structural playability but not factual accuracy, so the agent must escalate to the maker. That is a behavioral trait the annotations do not convey.

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?

Three tight sentences, front-loaded with the read-only nature and the check list before the caveat. The leading 'Read-only' is mildly redundant with annotations but otherwise every clause carries 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?

For a one-parameter, non-destructive validation tool this covers purpose, checked dimensions and a critical limitation. With no output schema, it does not say what a failure report looks like, which is the one remaining gap.

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% and the single quiz_id parameter is already documented as coming from create_quiz or list_quizzes, so the description adds no parameter-level meaning. Baseline 3 applies.

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?

States a concrete verb and resource ('Check a saved quiz for playability') and enumerates the exact aspects verified: answer counts, zero-based correct indexes, numeric estimate targets, timings and images. That enumeration distinguishes it from get_quiz (retrieval) and preview_quiz (rendering), though no sibling is named explicitly.

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?

'Check a saved quiz for playability' plus the 'schema-valid is not the same as factually correct' caveat gives a clear condition for use and warns against over-trusting the result. It stops short of naming an alternative or stating when not to call it (e.g. before vs. after publish).

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