Drug safety brief (bundle) — One call for a medication: RxNorm identity, FDA label safety text (boxed warning, warnings, interactions, contraindications) and the most-reported real-world adverse reactions (FDA FAERS). Reference data, not medical advice. JSON. Price: $0.05 USDC (Base, via x402).
| Name | Required | Description | Default |
|---|---|---|---|
| name | Yes | drug brand or generic name |
Changes observed during successful MCP inspections.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Beyond the annotations (readOnly, non-destructive, openWorld), the description adds valuable behavioral context: it returns reference data, is not medical advice, outputs JSON, and costs $0.05 USDC via x402. These details help an agent set expectations about safety, format, and cost. No contradictions with annotations.
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, well-structured sentence packs all essential information: scope, included data sources, output format, disclaimer, and pricing. The main descriptor is front-loaded, and every element earns its place. No fluff or redundant repetition of schema details.
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 simple one-parameter tool, the description covers the input, the output content, the format, and cost. It does not detail the exact JSON shape or error handling, but given there is no output schema, the high-level content list is sufficient for an agent to invoke it correctly. Minor gap: no mention of what happens for unknown drug names.
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 already provides 100% coverage with the parameter description 'drug brand or generic name'. The tool description adds little beyond that, mentioning 'a medication' but not specifying format variants, case sensitivity, or examples. Baseline 3 is appropriate since schema handles parameter semantics adequately.
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 what the tool delivers: a bundled drug safety brief with RxNorm identity, FDA label safety sections, and FAERS adverse reactions. It uses a resource-focused phrasing ('One call for a medication') and lists concrete components, making it easy for an agent to distinguish from sibling tools like fda_drug_label. The 'bundle' designation signals comprehensive coverage in a single call.
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 when to use this tool: when a comprehensive medication safety overview is needed in one call. It does not explicitly name alternatives or exclusion conditions, but the 'one call' phrasing implies it is the integrated option versus more focused tools. Clear context without explicit when-not guidance.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
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