Genomic-Agent-Discovery

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

No annotations provided, so description carries full burden. It discloses return data types (drug-gene interactions, dosing guidelines, clinical annotations) but omits operational details like error handling, 'not found' behavior, rate limits, or authorization requirements. 'Look up' implies 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?

Two sentences with zero waste: first establishes action and resource, second specifies output content. Front-loaded with verb, no filler words, appropriate length for single-parameter tool.

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 lookup tool with 1 parameter and no output schema, description adequately compensates by enumerating return data categories. Would benefit from mentioning error cases or empty result handling, but sufficient for 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% ('dbSNP rsID' fully documented), establishing baseline 3. Description mentions 'for a variant' which loosely maps to the rsid parameter but adds no validation rules, format examples, or semantic constraints beyond the schema.

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?

Description uses specific verb 'Look up' with explicit resource 'PharmGKB pharmacogenomic annotations' and distinguishes from siblings like query_clinvar/query_civic by naming the specific PharmGKB database and unique data types (dosing guidelines, drug-gene interactions).

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?

Implies usage domain through 'PharmGKB' specificity and clinical annotation focus, but lacks explicit when-to-use guidance or comparison to sibling pharmacogenomic tools (get_pharmacogenomics, get_cpic_drugs, query_civic). No exclusions or prerequisites stated.

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