cliniko_get_treatment_noteFetch a single treatment note by id. NOTE: treatment notes are protected health information (PHI). Read-only. GET /treatment_notes/{id}.
| Name | Required | Description | Default |
|---|---|---|---|
| id | Yes | Treatment note id. |
Changes observed during successful MCP inspections. Dates show when Glama detected each change.
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true, so the description's 'Read-only' is expected but redundant. It adds meaningful context by flagging treatment notes as protected health information (PHI), which is a useful behavioral and compliance cue. The HTTP endpoint also provides a concrete implementation detail beyond the 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?
The description is two short sentences with no wasted words. The core action is front-loaded, followed by the PHI warning and endpoint, making it easy to scan.
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 single-parameter read tool, the description is complete. It states what is fetched, by what identifier, that it is read-only, and that PHI sensitivity applies. No output schema exists, but the description sufficiently implies the return payload without needing to explain it.
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 coverage is 100% and the single 'id' parameter already has a clear description ('Treatment note id.'). The tool description adds no additional parameter meaning, so the baseline score of 3 is appropriate.
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 a specific verb ('Fetch') and resource ('a single treatment note by id'), making the action and scope clear. It also includes the HTTP endpoint, which reinforces the resource and distinguishes this tool from list-type siblings like cliniko_list_treatment_notes.
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 clearly indicates this tool is for fetching one treatment note by its id. It does not explicitly name alternatives or state when not to use it, but the 'by id' scoping is enough to guide an agent away from list operations for most cases.
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 resource-action pair such as patients, appointments, invoices, treatment notes, or availability. Even the two availability tools are clearly separated by description: list_available_times returns multiple slots while next_available_time returns one.
Tools consistently use the cliniko_ prefix with get_, list_, or create_ verbs before a resource name. The only notable deviation is cliniko_next_available_time, which lacks an explicit verb, but the overall pattern remains predictable and easy to navigate.
At 17 tools, the server is on the higher end but still reasonable for a practice-management API covering account info, businesses, practitioners, patients, appointments, invoices, treatment notes, products, and availability. Each tool maps to a meaningful endpoint, though next_available_time could be seen as partially redundant with list_available_times.
The core booking workflow is covered well: clients can look up availability and create appointments, and patient lookup is supported. However, there are no update, delete, or cancel operations for appointments or patients, and invoices and treatment notes are read-only, leaving notable lifecycle gaps.