get_pharmacogenomics

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

Despite no annotations, the description discloses internal operations: queries CPIC tables and checks patient genotypes. This provides good behavioral context for an AI agent, going beyond a simple 'get' statement.

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: first states purpose, second explains process. No redundancy, front-loaded. Every sentence adds value, making it highly concise.

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?

No output schema provided, and the description omits return format details or error conditions. For a complex tool involving multiple queries, the description is adequate but incomplete for an AI to fully anticipate results.

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?

Only one parameter 'gene' with full schema coverage. The description adds functional context (e.g., 'specific gene', 'allele definitions') but does not add new constraints or format details beyond the schema's example. 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?

Describes a specific verb ('Get') and resource ('pharmacogenomic results for a specific gene'). Details that it queries CPIC tables for allele definitions and drug recommendations, clearly distinguishing from sibling tools like get_all_pharmacogenomics or get_cpic_drugs.

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?

Implicitly suggests use for a single gene query, but does not explicitly state when to choose this over alternatives or provide exclusions. Sibling tools exist for bulk results or drug-focused queries, but no guidance is given.

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