Variant 3-D Structural Triage

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

Annotations already provide readOnlyHint and idempotentHint. The description adds that it returns a pathogenicity_tier with possible values and lists output sections. No contradiction; it enhances transparency by specifying output structure.

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 (approx. 15 lines) with clear bullet points, an example call, and 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 complexity (multiple data sources, nested output), the description covers the tool's purpose, inputs, output tier, and example. An output schema exists to detail the return structure, so the description is sufficiently complete.

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 all parameters (hgvs, include_*). The tool description adds no additional semantics for these parameters beyond summarizing the overall report content. Schema coverage is effectively 100% from the schema itself, so baseline of 3 is appropriate.

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 'Comprehensive clinical triage for a missense variant' and lists four specific data domains fused into a prioritized report. It distinguishes from siblings like classify_variant_acmg or generate_variant_clinical_report by emphasizing structural and multi-context integration.

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 explicitly frames the tool for clinical triage and details what it covers. However, it lacks explicit 'when to use vs. alternatives' or 'when not to use' guidance, leaving the AI to infer from the listed components.

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