gwas_variant_associations

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 does reveal what the tool returns (associated traits, p-values, risk allele frequency, effect sizes), but it does not mention behavior for invalid or missing variants, evolutionary/population scope, or limitations of the source data. This is adequate but not thorough.

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 short and front-loaded with the core action. The bilingual repetition adds some length but the Chinese portion also contributes meaning by adding the output fields and use cases. No filler or off-topic content is present.

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?

This is a simple one-parameter lookup tool with an output schema available. The description covers purpose, lookup key, example input, output content, and intended applications. For the tool's complexity, this is complete enough for an agent to invoke it correctly.

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 has only 'rsid' with no property description, and schema coverage is 0%. The description compensates by explaining that the input is a dbSNP number and provides a concrete example ('rs73229090'), which is sufficient for a single well-known identifier type. It could additionally specify strict format rules, but the example makes the intended input clear.

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 states a specific verb ('Get'), a concrete resource ('GWAS associations for a variant'), and a precise lookup key ('by rsID'). It also gives an example rsID and names the returned data fields, making the tool's role unmistakable and distinguishing it from related tools like gwas_gene_variants.

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 clearly frames when this tool is relevant: querying variant-level GWAS results for genetic association interpretation and Mendelian randomization studies. It does not explicitly name alternative tools for other use cases such as gene-level GWAS, so it falls just short of full exclusion guidance.

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