Lists treatments offered by the clinic, each with its canonical page URL.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
| Name | Required | Description | Default |
|---|---|---|---|
| data | Yes | ||
| meta | Yes | ||
| evidence | Yes |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, covering the safety profile. The description adds the behavioral context that the tool returns canonical page URLs for each treatment, which is useful beyond the annotations. It does not contradict any annotation and provides a bit of extra transparency about the output content.
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 of twelve words, front-loaded with the verb and resource. Every word adds value, and there is no repetition of schema information or filler. It is concisely structured without sacrificing clarity.
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 (no parameters, a clear read-only list operation), the description is complete. An output schema exists to describe the return structure, so the description does not need to detail return values. It sufficiently covers the purpose and the one key behavioral detail (canonical URL).
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 tool has zero parameters, so the baseline is 4. The description correctly adds no parameter information because there are none to clarify. The schema coverage is 100% trivially, and the description is consistent with the absence of parameters.
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 the specific verb 'Lists' with the resource 'treatments offered by the clinic' and adds the meaningful detail that each treatment comes with its canonical page URL. This clearly distinguishes it from sibling tools like get_prices or get_aftercare_information, which focus on different aspects of the clinic.
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 implies usage through its clear statement of what the tool does, but it does not explicitly state when to use this over alternatives like search or other get_* tools. There are no exclusions or 'instead of' guidance given, so the agent must infer based on the tool name and description.
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 get_* tool targets a distinct information domain (clinic profile, doctor profile, prices, reviews, etc.), but the generic 'fetch' overlaps with the specific getters, creating minor ambiguity.
Most tools follow a get_* pattern, but 'fetch' breaks the convention, and 'search' and 'request_callback' deviate from the get_ prefix, resulting in an inconsistent style.
With 12 tools, the set is well-scoped for a patient services server, covering information retrieval and contact actions without bloat.
The server covers the core patient journey: researching treatments, clinic info, prices, reviews, visit logistics, and initiating contact via callback or WhatsApp. A potential gap is direct appointment booking, but the contact mechanisms compensate.
