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

No annotations are present, so the description carries the full burden of behavioral disclosure. It goes beyond the schema by listing the return payload, revealing a known quirk about AQA Combined Science Trilogy Physics Paper 2, and explicitly scoping coverage to specific AQA specs. It does not describe behavior for unsupported topics, but the disclosed constraints are substantial.

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 purpose and remains tight despite covering multiple aspects: purpose, example, input, output, quirks, and supported specs. The example sentence earns its place by clarifying the tool's intent, and the coverage list is necessary for setting expectations. There is no redundancy or filler.

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 is no output schema and no annotations, the description sufficiently explains what is returned, what inputs are accepted, and which specifications are supported. It also communicates a known quirk that could otherwise surprise an agent. The definition is complete enough for an agent to select and invoke the tool correctly.

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 the baseline is 3. The description adds meaningful value by listing the exact covered specifications, which clarifies valid combinations of board, subject, and level. It also reinforces that board, subject, and level are optional alongside the required topic parameter, slightly exceeding what the generic schema examples provide.

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 immediately states the tool's core purpose in the form of a concrete question: which exam paper a topic is on. It then specifies the resource and result set: returns the paper, sibling topics, spec code, and official spec URL. This clearly distinguishes it from sibling lookup tools by focusing on topic-to-paper mapping.

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 gives clear context for when to use the tool: when a user has a topic and wants to know which exam paper it appears on. It also frames this as the canonical student revision question, signaling the intended use case. It does not explicitly name alternatives or state when not to use it, but the context is specific enough.

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