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

No annotations, so the description carries the burden and does add genuine behavioral context: dataset size (~450k), the fact that the PubMed domain is empty in practice, and the created_year semantics gotcha. Pagination caps and default limits are covered only by the schema, not the description, leaving some behavior to be inferred.

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?

Two compact sentences, front-loaded with purpose and dataset scale, followed by the two highest-value caveats. No filler text; every clause earns its place.

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?

For a search tool with full schema parameter coverage and no output schema, the description covers scope, size, and the key year caveat. It could mention the detail sibling (get_meeting_report_detail) for full records, but overall it is sufficient for correct invocation.

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 real meaning beyond the schema by clarifying that created_year (bound to year_from/year_to) is the ingestion year rather than publication year. This directly improves correct parameter interpretation.

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 (检索/search) plus resource (医学会议摘要, 45万条, ASCO/ESMO/SABCS), and explicitly distinguishes its domain from the PubMed sibling by noting rs_pubmed is empty. An agent can identify the resource and scope without opening the 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?

Provides clear usage context: what the domain contains (only conference abstracts, no PubMed) and a critical semantic caveat that created_year is ingestion year, not publication year. However, it does not name an explicit alternative when the agent needs full records or PubMed data, so the routing guidance is incomplete.

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