Returns connection status and URLs. When all providers are connected, returns authenticated:true and empty pending[]. When credentials are missing, returns connect_url for the toolkit and per-install URLs.
| Name | Required | Description | Default |
|---|---|---|---|
No arguments | |||
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint, idempotentHint, destructiveHint, indicating safe, idempotent read operation. The description adds behavioral context by detailing response fields (authenticated, pending, connect_url) and explaining different states, going beyond 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?
Two sentences, front-loaded with the main action. Every sentence provides essential information without redundancy. Highly concise and well-structured.
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 no output schema, the description explains key return scenarios (authenticated state, pending array, connect URLs). It covers the necessary context for an agent to interpret results correctly. Complete for a simple status check tool.
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 has zero parameters, and schema description coverage is 100% (trivially). Per guidelines, zero parameters earn a baseline of 4. The description adds no parameter semantics, but none needed.
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 the tool 'Returns connection status and URLs', specifying the verb (returns) and resource (connection status). It distinguishes itself from siblings like 'authenticate' by focusing on status rather than performing authentication. Additional details about different response scenarios add clarity.
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 context on when to use the tool by explaining behavior under different conditions (all providers connected vs missing credentials). However, it does not explicitly mention when not to use it or offer alternative tools, leaving some guidance implicit.
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.
Many tools have identical descriptions (e.g., multiple tools with same 'Read appointments and scheduling data' text) and only differ by a 'flattened action' label, making it impossible for an agent to distinguish which tool to call for a specific operation.
Names follow a loose verb_noun pattern but are extremely inconsistent: some use underscores, some have redundant prefixes like 'feegow_appointment_', and the same actions are duplicated across multiple tool names (e.g., 'list' appears in many). The 'flattened action' suffix is confusing.
94 tools is far too many for a clinic management system. This is clearly due to a one-action-per-tool design that fragments the API surface, making the server bloated and hard to navigate. A typical well-structured server for this domain would have 10-20 tools.
The server covers many areas (appointments, patients, financial, procedures, stock, etc.), suggesting broad functionality. However, the fragmentation obscures gaps and makes it difficult to determine if all CRUD operations exist for each entity. Some areas (e.g., stock write) have multiple tools for single actions.