Genomic-Agent-Discovery

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

With no annotations provided, the description carries the full burden and successfully discloses return content ('pharmacogenes mapped to their affected medications with clinical guideline levels'). However, it omits operational details like data freshness, caching behavior, or error conditions.

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 efficiently structured sentences with zero waste: the first defines the resource and return structure, the second specifies the clinical use case. Information is front-loaded appropriately.

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?

Strong coverage given no output schema exists: the description compensates by detailing the return structure (genes mapped to medications with guideline levels). Minor gap in not explaining what 'CPIC' stands for or the significance of 'clinical guideline levels' for users unfamiliar with pharmacogenomics nomenclature.

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 input schema has 100% description coverage for the single optional 'gene' parameter. The description does not add parameter-specific semantics, but the guidelines specify a baseline of 3 when schema coverage is high (>80%) and the schema already documents the filtering behavior.

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 uses a specific verb ('Get') and resource ('CPIC gene-drug interaction lookup table'), clearly distinguishing it from sibling tools like get_pharmacogenomics or query_pharmgkb by specifying the CPIC (Clinical Pharmacogenetics Implementation Consortium) guideline source.

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 clear usage context ('Use this to identify drug interaction risks for a patient's metabolizer profile'), but lacks explicit comparison to alternatives like get_pharmacogenomics or query_pharmgkb, or guidance on when CPIC guidelines are preferred over other databases.

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