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

Annotations already declare readOnlyHint, idempotentHint, destructiveHint=false and openWorldHint=false, so safety is covered. The description adds genuine behavioral detail: the exact fields matched, the special PMID/DOI short-circuit behavior, and the shape of the result ('summary records with evidence codes and URLs'). It omits the 50-result cap, but that is disclosed in 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 sentences, front-loaded with purpose and filters before the field enumeration. The long third sentence listing searchable fields is dense but each item is decision-relevant, so little is wasted.

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 and 7 optional parameters, the description compensates by naming the return format and the identifier special case. Pagination is delegated to the offset schema description, which is a reasonable split, though a brief note on result volume/next_offset would close the 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?

The description adds meaning beyond the schema: it maps the entity filter to gene/drug/disease and clarifies author matching accepts both the author-list form "Sabatini DM" and full names. Evidence code, year range and keyword semantics are named, giving conceptual coverage of most of the 7 parameters on top of the 71% schema coverage.

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 (search) and resource (curated studies), then enumerates the filter dimensions (keywords, evidence code, linked entity, year range) and the searchable fields. An agent can distinguish it from get_study (single record) and from search_authors/search_entities without opening any 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?

Usage is implied through the filter list and the note that a PMID/DOI query returns that study, which tells the agent a lookup-style query is valid here. However, it never states when to prefer get_study over this, nor any exclusions or prerequisites, leaving routing to inference.

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