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

Annotations already declare readOnlyHint=true and openWorldHint=false, so safety is covered. The description adds genuine behavioral context: results are deduplicated to one sample per question type, each sample carries prompt, audio/image, tags, difficulty and frequency, and answer keys/explanations are deliberately excluded — a constraint an agent cannot infer from the schema.

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: capability and filter axes first, then result shape, then the exclusion caveat. Every sentence carries information that changes how an agent calls or interprets the tool; nothing is repeated boilerplate.

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 takes on the return-value burden and does so well by naming the fields per sample and the one-per-type cardinality. Minor gaps remain: it does not say how multiple filters combine or what an empty result looks like, though the limit cap is documented in the schema.

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 every parameter has its own description including the limit cap, so the schema does the heavy lifting. The description restates the filterable dimensions (question type, skill category, difficulty, prediction status, keyword) without adding semantics such as matching behavior, enum interpretation, or how filters combine — baseline 3.

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 specific verb and resource (find public PTE Academic sample questions) plus the dimensions it can be filtered on, and defines the granularity of the result ('one representative sample per question type'). It is unmistakably distinct from the siblings get_score_requirements, get_test_format and list_question_types, which retrieve reference data rather than search samples.

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?

Usage is implied by the filter list and by the exclusion note 'Answer keys and explanations are not included', which implicitly routes answer-key needs elsewhere. However, there is no explicit when-to-use versus list_question_types or get_test_format, and no statement of prerequisites or when to omit filters.

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