variant_getter

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It describes what information is retrieved (gene location, population frequencies, clinical significance, etc.) and mentions the tool accepts multiple ID formats, which adds useful context. However, it doesn't disclose important behavioral traits like rate limits, authentication requirements, error conditions, or whether this is a read-only operation.

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 perfectly structured and concise. It starts with a clear purpose statement, then provides a bulleted list of what information is retrieved, and ends with specific ID format examples. Every sentence earns its place with no wasted words, and information is front-loaded effectively.

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 that an output schema exists (so return values don't need explanation in the description), the description provides good context about what information is retrieved and how to format inputs. However, for a tool with no annotations and potentially complex genetic data, it could benefit from more behavioral context about limitations, data sources, or typical use cases.

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 schema description coverage is 100%, so the schema already documents both parameters well. The description adds meaningful context by listing the specific ID formats accepted (HGVS, rsID, MyVariant ID) and mentioning what 'external annotations' include (TCGA cancer data, conservation scores), which provides additional semantic understanding beyond the schema's technical descriptions.

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's purpose with specific verbs ('fetch comprehensive details', 'retrieves all available information') and identifies the resource ('specific genetic variant'). It distinguishes itself from sibling 'variant_searcher' by focusing on detailed retrieval for a single variant rather than searching.

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 provides clear context for when to use this tool (to get comprehensive details for a specific variant) and implies when not to use it (for searching multiple variants, which would use 'variant_searcher'). However, it doesn't explicitly name alternatives or provide exclusion criteria beyond the implied distinction.

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