get_hospital_cliniciansClinicians affiliated with a hospital (CMS data): name, specialty, Medicare procedure volumes, Open Payments totals. Available for ~4,570 hospitals (clinicians_tool_available flag). Filter matches name or specialty.
| Name | Required | Description | Default |
|---|---|---|---|
| ccn | Yes | Hospital CCN (6 characters). | |
| limit | No | Max clinicians (default 20). | |
| filter | No | Optional case-insensitive substring on name or specialty. |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
With no annotations provided, the description carries the burden of behavioral disclosure. It reveals the data source (CMS), availability constraints, and filter semantics, but it does not specify that this is a read-only operation or describe any side effects, error handling, or response format. This adds some context but leaves significant behavioral aspects undocumented.
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 two sentences, concise and front-loaded. The first sentence states the core purpose and the second adds the availability flag and filter behavior. Every word contributes value, and it is appropriately sized for the tool's complexity.
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 retrieval tool with three parameters and no output schema, the description covers the main aspects: what data is returned, the data source, availability caveat, and filtering. It doesn't explain default limits or response structure, but those are partly covered by the schema. It is complete enough for most uses, with minor gaps.
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 minimal parameter-related detail beyond the schema: it reiterates the filter behavior already in the schema and doesn't clarify ccn or limit semantics beyond what's described. Thus, it provides modest additive value.
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 explicitly states the tool retrieves clinicians affiliated with a hospital, listing the data fields (name, specialty, Medicare procedure volumes, Open Payments totals). The title and name reinforce this, and the content clearly distinguishes it from sibling tools like get_facility or get_hospital_prices.
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 provides clear use context: it returns clinician data from CMS, available for ~4,570 hospitals with a flag. It also explains the filter behavior. However, it does not explicitly state when to avoid this tool or mention alternatives, so it stops short of a full 5.
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 serves a clearly distinct purpose: search discovers facilities, get_facility provides metadata and tool compatibility, get_facility_profile returns detailed profiles, and the two hospital-specific tools cover clinicians and pricing. There is no meaningful overlap between these five operations.
All tool names follow a consistent verb_noun pattern: get_facility, get_facility_profile, get_hospital_clinicians, get_hospital_prices, and search_facilities. The naming is uniform and predictable.
With five tools, the server is well-scoped for its purpose of facility lookup and hospital-specific data retrieval. Each tool covers a distinct aspect without redundancy or bloat.
The set covers search, lookup, profiles, and specialized hospital data (clinicians and prices), providing a complete workflow for hospital facilities. Minor gaps exist for non-hospital facility types, which only have profile access and no specialized data tools, but this appears driven by data availability rather than an oversight.