clinvar_query

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

No annotations are provided, so the description must carry the behavioral burden. It does disclose that the tool queries NCBI E-utilities and returns clinical significance categories, which is valuable. However, it does not mention important operational details such as rate limits, whether results are limited by max_results, or the exact output format, leaving some behavior unspecified.

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 fairly short and front-loaded, but it repeats the same meaning in English and Chinese, creating redundancy. The bilingual content may serve multilingual users but adds token overhead for an AI agent without adding new information.

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?

For a simple two-parameter query tool with an output schema, the description covers the essential context: what is being queried, what input is expected, what output is returned, and the intended clinical interpretation use case. The main gap is the lack of detail on max_results and potential result-count limits, but the overall context is sufficient for correct usage in most 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?

Schema description coverage is 0%, so the description must compensate. It does explain the main 'query' parameter as accepting a gene name or variant, and 'max_results' is self-explanatory with a default in the schema. However, max_results semantics are not described in the text, and the description does not fully clarify query syntax or accepted variant formats.

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 function: querying ClinVar clinical variants via NCBI E-utilities and returning clinical significance classifications. It specifies the resource, the action, and the key output. It does not explicitly contrast itself with sibling tools like dbsnp_search or variant_annotate, but the focus on ClinVar and clinical interpretation makes it reasonably distinguishable.

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 gives a clear use context: 'for clinical variant interpretation' / '用于变异临床解读'. It also states the input type (gene name or variant), which helps an agent decide when to call it. It does not explicitly state when not to use it or name alternative tools, but the context is clear enough for selection.

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