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

No annotations are provided, so the description carries full burden. It discloses the tool returns many data types, explains optional breed_context and cross_breed_full behaviors, and notes the default for top_n. It does not mention potential performance considerations or rate limits, but is otherwise transparent.

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 a single, dense sentence that front-loads key information and packs in all details without wasted words. Every phrase 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 output schema exists, the description does not need to detail return values. It covers all tool capabilities and parameter behaviors, making it complete for a complex tool with four parameters.

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 fully compensates by explaining all four parameters: position format, breed_context string behavior, cross_breed_full boolean effect (all 188 breeds vs top_n), and top_n default (5). This adds significant meaning beyond the bare schema.

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 returns comprehensive variant data for a CanFam4 position, listing all included fields (frequency, pathogenicity, gene context, diseases, provenance, deep links). It distinguishes from siblings by being the 'headline query' that bundles multiple data types in one call.

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 implies this tool is for comprehensive variant context, but does not explicitly state when to use alternatives like variant_lookup or breed_variant_frequency. However, the context of sibling tools and the phrase 'headline query' provide clear usage direction.

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