count_variants

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

With no annotations provided, the description carries the full behavioral burden. It discloses that counting is server-side, that nothing is downloaded, and that omitting filters returns the total variant count. This gives agents an accurate model of the operation's behavior and side effects.

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 dense but well-organized, front-loading the core purpose and then grouping related filter parameters. Each sentence contributes useful information, though some parameter details overlap with the schema descriptions.

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 presence of an output schema and a 100% schema-covered input, the description provides all the contextual information an agent needs: what the tool does, when to use it, how filters compose, and where identifier values come from. Nothing essential is missing.

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?

Schema coverage is 100%, but the description adds meaningful context beyond the schema: it states that reference_name, start, and end come from list_sequences, that variant_set_db_id is a BrAPI variantSetDbId from list_variant_sets/list_content, and that no filters yields the total count. This helps agents correctly map parameters to domain sources.

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 a specific verb plus resource ('Count variants matching filters') and clearly states what makes it distinct: it is computed server-side and nothing is downloaded. This makes it easy to differentiate from siblings like search_variants or export_genotypes.

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 this as 'a fast way to size a query before pulling data,' which gives clear guidance on when to use it. It does not name specific sibling alternatives that should be used instead, but the use case is sufficiently clear.

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