search_entities

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

Annotations already cover read-only/idempotent/non-destructive behavior. The description adds per-query constraints such as 'requires doi_a and doi_b' and 'requires doi', which are behavioral details beyond the bare 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?

The description is compact, front-loaded with the primary purpose, and uses a list to present query types efficiently. The inline list is dense but each clause adds needed routing information.

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 read-only tool with an output schema, the description provides enough context to choose a query type and identify required DOI inputs. Minor gaps remain around limit and entity field usage, but the main invocation path is fully specified.

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 parameter descriptions are absent (0% coverage), and the description compensates by mapping query_type values to their intended fields and required DOI parameters. It does not explain the limit parameter or explicitly bind entity_name/entity_type to their query modes, leaving some semantics to inference.

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 object ('biomedical entity graph') and enumerates five concrete query modes with their outcomes. It clearly distinguishes entity-graph search from generic search tools by specifying user intents (papers, co-occurrences, shared entities).

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 explicit 'Use this when...' triggers for entity-relationship questions and explains which query type fits which request. It does not name sibling alternatives or state when not to use it, so it omits exclusionary guidance.

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