Drug patent expiries ranked by the Medicare Part D spending exposed to them
Scored across 1 tool
With only a single tool, there is no possibility of overlap or confusion with other tools. The tool's purpose is unambiguous and clearly stated.
The lone tool name follows a clear, descriptive noun-based pattern. With no other tools to compare against, naming inconsistency is not a concern.
The server is scoped to a single, highly specific analytical task, so one tool is arguably appropriate. However, it is on the thin side and slightly under the typical useful range for a server.
The tool covers the core advertised functionality of ranking LOE exposure by Medicare Part D spending. It lacks additional capabilities such as filtering by drug, date range, or drilling into individual drug details, which are notable gaps for realistic use.
Rank upcoming FDA Orange Book patent and exclusivity expiries BY the gross Medicare Part D spending exposed to them, with marketed-generic status for each ranked drug resolved from live CMS NADAC price evidence. Answers which expiries matter, not merely which come first. Reports EXPOSURE, never forecast savings. Spending is gross of manufacturer rebates. Orange Book small molecules only, so biologics — among the largest Part D line items — are excluded, and the headline total must not be read as spending that will "go generic".
| Name | Required | Description | Default |
|---|---|---|---|
| limit | No | How many drugs to rank, default 25 | |
| window | No | Months ahead to include, default 24 |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the full burden of behavioral disclosure, and it does a strong job: it clarifies that spending is gross of manufacturer rebates, that this is not a savings forecast, that only Orange Book small molecules are included, and that biologics are excluded. It does not mention output format, pagination, or potential failure modes, which prevents a 5.
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 front-loaded with the core purpose and ranking criterion, and each subsequent sentence adds a distinct caveat or clarification. There is no redundant or filler text, and the structure moves logically from what it does, to its ranking philosophy, to its important limitations.
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 tool with two optional parameters, no output schema, and no sibling tools, the description provides robust context: the ranking basis, the data source for generic status, the spending measure, and the exclusions. It does not state how results will be returned or how the limit/window parameters affect the output, but overall it is sufficiently complete for an agent to understand the tool's scope and intent.
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 documents both parameters with 100% coverage, including defaults ('default 25', 'default 24'), so the baseline is 3. The description does not add any extra semantics about how limit or window behave, but this is not a significant gap given the schema is complete.
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 states a specific verb ('Rank') applied to a specific resource (upcoming FDA Orange Book patent and exclusivity expiries) with a clear ranking criterion (gross Medicare Part D spending exposure). It also distinguishes itself from a mere chronological expiry list by saying it 'answers which expiries matter, not merely which come first.'
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 gives clear context for when to use the tool: when prioritization by Part D spending exposure is needed rather than chronological ordering. It also provides explicit exclusions and caveats, such as small molecules only, biologics excluded, and that it reports exposure rather than savings forecasts. There are no named alternatives, but the negative guidance effectively clarifies what this tool is not for.
Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.
Recent tool additions, removals, and schema changes observed during successful MCP inspections.
loss_of_exclusivity_exposureUS drug price benchmarks — what a pharmacy PAYS and what Medicare PAYS OUT.
Whether a drug has a marketed generic today, and when its Orange Book protections lapse
CMS Medicare Part D drug spending and prescriber data. 2024 quarterly data.
Medicare spending, chronic conditions, hospital quality, readmissions, and enrollment
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