Resolve a brand or generic drug name to its canonical RxNorm record: RxCUI, generic name, brand names, synonyms.
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | Brand or generic, e.g. 'Tylenol' or 'acetaminophen'. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries full burden. It mentions output fields but does not disclose whether the tool is read-only, error behavior, case sensitivity, or any constraints. The description is too minimal to provide adequate behavioral transparency.
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?
The description is a single sentence, 14 words, front-loaded with the action and output. Every word is useful, no redundancy. Efficient and clear.
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?
Given the tool's simplicity (one parameter, no output schema), the description lists the expected output fields (RxCUI, generic name, brand names, synonyms) which provides sufficient completeness. It could mention output format but is otherwise adequate.
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 describes the 'name' parameter with examples. The description does not add extra meaning about the parameter beyond what the schema provides, so 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?
The description uses a specific verb 'Resolve' and explicitly states the resource (drug name) and the output (canonical RxNorm record with RxCUI, generic name, etc.). It clearly distinguishes from sibling tools like check_interaction which are for interaction checking.
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 implicitly indicates usage for normalizing drug names, but does not explicitly state when to use this tool versus the siblings (check_interaction, check_interactions_multi). No when-not-to-use or alternative conditions are mentioned.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Add one secure layer between your agents and this server.
Each tool has a distinct purpose: single pair, multi-pair, and name normalization. No overlap or ambiguity.
All tools follow a consistent verb_noun snake_case pattern (check_interaction, check_interactions_multi, normalize_drug_name).
Three tools are well-scoped for a drug interaction checker: one for single pairs, one for batch checks, and one for name resolution.
Covers the core workflow: name lookup, single interaction, and batch interaction. Missing a tool to retrieve all interactions for a drug, but the multi tool can handle it with multiple calls.