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

Annotations already establish read-only, idempotent, closed-world behavior, and the description adds meaningful context beyond that: the evidence provenance returned (CPIC/DPWG guideline, drug label, primary literature) and the fact that genotype input is not required. It goes beyond the safety profile into actual result semantics.

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?

A single front-loaded sentence that names the input, the three returned facets, and the genotype constraint without filler. Slightly dense with clauses, but every clause carries information.

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 one-parameter read tool with no output schema, the description explains what comes back conceptually (genes, evidence basis, uncovered drugs) and that no genotype is needed. Only the batch-size limit is left to the schema, which is appropriate.

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% and the schema already documents the medications array with an example and min/max constraints. The description reinforces 'generic drug names', which adds a small amount of meaning (generic vs. brand) but largely restates 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?

Specific verb (screen a list) plus a precise statement of the output: which drugs have a curated drug–gene record, the associated genes, the evidence basis, and which are not covered. This clearly separates it from the single-item siblings like lookup_drug_gene.

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 conveys the batch-screening context ('Given a list of generic drug names') and states the precondition 'Needs no genotype', which is useful. However, it never explicitly contrasts with lookup_drug_gene or list_genes, so the agent must infer that this is the bulk variant.

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