uniprot_get_disease_associations

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

Annotations declare readOnlyHint and openWorldHint; the description adds context about the curated nature of results and handling of empty results, going beyond annotations without contradiction.

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?

Concise, front-loaded description with no filler. Every sentence adds value, including the note about alternative sources.

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?

Covers return fields, clinical relevance, and interpretation of empty results. With an output schema present, the description is sufficiently complete, though parameter explanation is missing.

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 0%, and the description does not explain the 'response_format' parameter (default 'markdown') or its impact on output format. The 'accession' parameter is implied but not explicitly described.

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 clearly states it returns structured disease associations for a UniProt entry, listing specific fields (name, acronym, etc.) and distinguishes it from raw cross-references, making the purpose very specific and unambiguous.

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 explicit guidance on when to use this tool (clinical interpretation, literature-anchored associations) and when not (empty result does not imply disease-irrelevant, with alternative sources like Open Targets, OMIM, DisGeNET mentioned).

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