Genomic-Agent-Discovery

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

No annotations provided, so description carries full burden. 'Look up' and 'Shows' imply read-only behavior, and the description compensates for missing output schema by listing return fields (pathogenicity, phenotypes, review status). However, lacks explicit safety declarations, auth requirements, or rate limits.

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?

Two sentences with zero waste. First sentence establishes purpose; second sentence details output. Every word earns its place.

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 single-parameter tool with full schema coverage and no output schema, the description adequately compensates by detailing the three specific data categories returned. Missing annotations slightly lower the score, but sufficient for this complexity level.

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% with 'rsid' described as 'dbSNP rsID'. Description mentions 'variant' which aligns with the parameter semantics, but does not add syntax details, format constraints, or examples beyond what the schema already provides. Baseline 3 is appropriate.

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?

States specific verb ('Look up') + resource ('ClinVar clinical significance') + scope ('for a variant'). Naming the specific database 'ClinVar' distinguishes it from sibling tools like query_alphamissense or query_cadd.

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?

Provides implied usage by specifying the unique data returned (pathogenicity classifications, star ratings), allowing inference that this is for clinical significance queries. However, lacks explicit when-to-use guidance or contrasts with sibling variant query tools.

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