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

Without annotations, the description discloses key behaviors: it performs hybrid + semantic ranking, returns ranked entities with snippets and links, and uses OData facets. It does not cover rate limits or auth, but as a read tool this is sufficient.

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 description is concise (about 100 words) and front-loaded with purpose and usage. It flows logically from purpose to parameters to output. Slightly dense but efficient.

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?

Given an output schema exists, the minimal output mention suffices. Parameter explanations are thorough, and usage context is provided. Could enhance with explicit sibling tool differentiation.

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?

With 0% schema description coverage, the description compensates well: it explains entity_type values (disease|breed|discovery), details filters syntax with examples, and implies query and top_k roles. However, explicit mention of top_k is missing.

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 is a 'Faceted hybrid + semantic-ranker search over the whole knowledge base' with specific examples of fuzzy/thematic intents, distinguishing it from sibling tools like search_diseases or breed_similarity by its broad scope and semantic ranking.

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 provides usage examples for fuzzy/thematic intent but does not explicitly state when not to use it or name alternative tools. The guidance is implied rather than explicit, missing clear differentiation from siblings.

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