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

Annotations already establish read-only, idempotent, non-destructive, closed-world behavior, so the bar is lower. The description adds genuine value beyond that: it discloses known data quirks (AQA Combined Science Trilogy Physics Paper 2 has no Space physics) and an explicit board/subject coverage boundary, which an agent needs to avoid over-trusting results.

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 core answer is front-loaded as a one-line question, then the return shape, then the coverage list. Every sentence earns its place except the coverage enumeration, which is dense but genuinely useful for scoping. Slightly long, but no 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?

With no output schema, the description compensates by naming exactly what is returned (paper, sibling topics, spec code, official spec URL) and disclosing board/subject coverage limits. For a 4-parameter lookup tool with full schema coverage and read-only annotations, this is nearly complete; only ambiguity handling (e.g. unknown topics, wrong-board inputs) is unaddressed.

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 100%, and all four parameters carry their own examples in the schema, so the baseline is 3. The description restates the same fields ("topic plus optional board/subject/level") without adding syntax, casing normalization, or matching behavior (e.g. whether 'aqa' vs 'AQA' matters), so it adds no meaning beyond the schema.

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 opens with a concrete question-answer framing ("Which exam paper is a topic on?") and enumerates the returned fields (paper, sibling topics, spec code, spec URL), so the resource and output are unambiguous. It does not explicitly distinguish itself from siblings exam_paper_index or exam_spec_lookup, whose names suggest overlapping territory (spec codes/URLs), so it stops short of a 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 gives a canonical call example ("is electricity paper 2 AQA?" → no, Paper 1) and states the input shape (topic plus optional board/subject/level), which makes the usage context clear. The explicit coverage list also tells the agent when the tool applies and when it will not. No alternative tool or exclusion condition is named, but the context is otherwise clear.

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