Read financial data in Feegow. Actions:
list_suppliers, search_supplier, list_categories, list_cost_centers, list_transfers, list_invoices, list_current_accounts, find_invoice_nfse, list_credit_card_brands, list_vouchers, list_sales, list_private_tables, get_dmed. All params are passed as JSON in the "data" field.
[Flattened action: list_invoices]
| 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 idempotentHint=true, indicating safe reading. The description adds 'Read financial data' but no further behavioral details 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?
The description is cluttered with a long list of unrelated actions that are not part of this tool. It could be a single sentence: 'List invoices. Params are passed as JSON in the data field.' Current version wastes space.
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 2-parameter read tool, the description should explain what list_invoices does (e.g., filters, pagination) and the meaning of parameters. It fails to provide this, leaving the agent underinformed.
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 0%. The description says 'All params are passed as JSON in the data field', which clarifies the data parameter but not the account parameter. No explanation of expected JSON structure or parameter purpose.
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 tool name 'feegow_financial_list_invoices' clearly indicates it lists invoices, but the description includes many other actions (list_suppliers, etc.) making the purpose ambiguous. The '[Flattened action: list_invoices]' helps, but the rest is confusing.
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 guidance on when to use this tool vs alternatives like feegow_financial_list_suppliers. The description does not differentiate it from siblings.
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.