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

Annotations already cover safety (readOnly, idempotent, non-destructive, closed-world), and the description adds substantive context beyond them: papers are returned newest first with each paper's role, `evidence` is structured and never a grade, and counts reflect only papers AgingResearch.News has read rather than all literature. That last caveat materially shapes interpretation of the 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 opening cue sentence and the find_entities sourcing note are front-loaded, with caveats and exclusions trailing sensibly. The long enumeration of example questions is dense but each item maps to a distinct capability, so little is wasted, though it is on the longer side.

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?

There is no output schema, so the description carries the return-shape burden, and it does: entity plus papers, newest first, per-paper role, and the nature of `evidence`. With annotations covering the safety profile, an agent has everything needed to call this correctly and interpret the response.

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, but the description adds semantics the schema lacks: it explains that type/key come from find_entities and illustrates valid pairings ('intervention rapamycin'). It does not discuss limit, cursor, or min_relevance in prose, though those are fully documented in-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 states a specific verb+resource (retrieve one entity and its papers) and enumerates the entity kinds covered (drug, supplement, gene, process, disease). It explicitly contrasts with find_entities as the discovery step that supplies type and key, so an agent can distinguish it from siblings without opening a schema.

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?

It gives the triggering condition ('questions about one drug, supplement, gene, process or disease'), names the upstream alternative ('Takes a type and key from find_entities (intervention rapamycin)'), and states an exclusion ('Not for personal medical advice or doses'). Both when-to-use and when-not are present.

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