Read benefit card data in Feegow (contracts and plans). Actions:
list_contracts: list benefit contracts. Filter by page, perPage, document, planId, name, personID, accountOwner, registrationNumber, initialDate, endDate, statusContractId, unity, user, accountPayer.
list_plans: list benefit plans. Filter by page, perPage, id.
[Flattened action: list_plans]
| Name | Required | Description | Default |
|---|---|---|---|
| data | No | ||
| account | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already declare readOnlyHint=true and destructiveHint=false, so basic safety is covered. The description adds minimal context ('Read') beyond annotations, but does not provide additional behavioral details like pagination or authorization.
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?
Description is short but includes extraneous mention of list_contracts, which may not belong to this tool. Front-loaded with 'Read benefit card data' but lacks focus.
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 only 2 parameters with no schema descriptions and no output schema, the description should explain the parameters and return format. It fails to do so, and the listed filters do not correspond to the actual schema.
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?
Input schema has 2 parameters (data, account) with 0% coverage. Description lists filters (page, perPage, id) that do not match schema parameters, causing confusion. No useful meaning added to actual 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 states 'Read benefit card data' but is ambiguous whether it lists contracts and plans or just plans, given the name and '[Flattened action: list_plans]' note. It does not clearly distinguish from the sibling tool 'feegow_benefit_card_list_contracts'.
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?
No explicit guidance on when to use this tool versus alternatives like 'feegow_benefit_card_list_contracts'. The description simply lists actions without context.
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.