Query Variant Research Database

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

Annotations already provide readOnlyHint and idempotentHint. The description adds that no API calls are made and data is from local SQLite, which is useful but does not go beyond the annotation's safety profile significantly.

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 5 sentences with clear front-loading of purpose. Every sentence adds value: purpose, data source, and integration context. No redundancy.

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 simplicity, rich schema, presence of annotations, and output schema, the description covers the essential aspects. It explains the local nature and data pipeline connection, making it complete for agent use.

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 includes detailed parameter descriptions (gene, tier, clinvar_class, etc.). The tool description does not add new parameter-specific meaning beyond the schema, but it provides context about the data source and integration with another tool.

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 the tool searches the local knowledge graph for previously analyzed variants, with specific verb 'search' and resource 'variants'. It distinguishes itself from siblings like generate_variant_clinical_report by emphasizing local query of stored results.

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 explains when to use: for searching previously analyzed variants from local storage (no API calls). It provides context about longitudinal research but does not explicitly state when not to use or name alternatives. Sibling list provides context.

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