Find Drug-Gene-Disease Network

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

Annotations already declare readOnlyHint and idempotentHint, so the description correctly aligns. It adds valuable context about using a local knowledge graph built from research sessions, which explains the behavior and scope beyond the annotations.

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 exceptionally concise (three sentences, ~60 words), front-loaded with the primary action, and contains no redundant information. Every sentence adds value.

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 the tool's moderate complexity, the description sufficiently covers the traversal concept, seed types, and the personal research history aspect. An output schema exists, so return values need not be explained. No significant gaps remain.

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 input schema already provides detailed descriptions for both parameters (seed types and max_hops constraints). The tool description merely echoes 'max_hops' without adding new semantic value, meeting the baseline for high 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?

The description uses specific verbs 'traverse' and 'expands' to indicate graph exploration from a seed entity. It clearly distinguishes this tool from sibling tools like 'lookup_disease' or 'get_disease_targets' by emphasizing hidden connections in a drug-gene-disease graph, making its purpose unique and well-defined.

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?

The description states it reveals hidden connections from your own research history, implying use for exploratory network analysis. While it does not explicitly exclude alternatives, the context is clear enough for an AI to differentiate from direct lookup or repurposing tools.

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