Get drug label, safety info, adverse events, or recall data from OpenFDA. Returns brand names, generic name, indications, warnings, dosage, interactions.
| Name | Required | Description | Default |
|---|---|---|---|
| name | No | Drug name (e.g. metformin, aspirin, lisinopril) | metformin |
| type | No | label (default), adverse_events, or recalls | label |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
No annotations are provided, so the description must fully disclose behavior. It lists return fields, but the list appears specific to the default 'label' type and may not apply to adverse_events or recalls, creating an overgeneralization. It also does not mention error behavior, limitations, or that output varies by type.
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, front-loaded with the primary action and scope, followed by a concise list of return fields. No filler or unnecessary repetition.
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?
The tool is simple with no required parameters and full schema coverage, and the description provides a purpose and return-field list, which is helpful given no output schema. However, it lacks clarity on how return fields vary by type and provides no usage guidance, so it is only minimally complete.
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 description coverage is 100%, so the baseline is 3. The description adds the OpenFDA context and mentions data categories, but it does not add meaning beyond the schema's parameter descriptions for name and type.
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 clearly states the tool gets drug label, safety info, adverse events, or recall data from OpenFDA, which is a specific resource and scope. It does not explicitly differentiate from sibling tools like get_compound_data or get_drug_targets, but the OpenFDA source and data categories provide reasonable clarity.
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?
No guidance is given on when to use this tool versus alternatives. It does not mention when to choose get_drug_info over get_compound_data or get_drug_targets, nor any exclusions or prerequisites.
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 targets a distinct data source and aspect: PubChem for chemical compound data, OpenFDA for regulatory and safety info, and ChEMBL for target and bioactivity data. There is no overlap in their purposes, making selection unambiguous.
All tools follow a consistent get_<object>_<data_type> pattern: get_compound_data, get_drug_info, get_drug_targets. The verb is always 'get' and the uses snake_case throughout, creating a predictable and uniform naming scheme.
With only 3 tools, the server is compact but covers three major drug-related databases. While a few more tools might round out the domain, the current count is reasonable and each tool earns its place.
The server covers chemical data, regulatory/safety information, and target/bioactivity data, providing a solid core for drug information retrieval. It lacks some common operations like search or batch retrieval, but for the stated purpose of getting specific data, the coverage is strong.