List all accepted insurance plans (convênios) and their sub-plans in Feegow. Optional filter by unidade_id.
Bulk support: accepts unidade_ids for batched execution.
| Name | Required | Description | Default |
|---|---|---|---|
| account | No | ||
| unidade_id | No | ||
| unidade_ids | No |
Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?
Annotations already provide readOnlyHint, idempotentHint, and destructiveHint. The description adds value by specifying that it lists all accepted plans, including sub-plans, and highlights batch execution via unidade_ids. No contradiction.
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 with no extraneous information. Front-loaded with purpose and action, then adds batch detail. Every sentence earns its place.
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?
No output schema exists, and the description does not describe the response format (e.g., fields like plan name, sub-plans, ID). Also lacks error conditions or prerequisites. For a read tool with no schema guidance, this is insufficient.
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?
With schema description coverage at 0%, the description should explain all parameters. It covers unidade_id and unidade_ids but does not mention the 'account' parameter. This omission limits the agent's ability to use the tool correctly.
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 it lists accepted insurance plans and sub-plans, using a specific verb-resource combination. It distinguishes from sibling tools like feegow_professional_insurance (professional-level) and feegow_procedure_insurance_list (procedure-level) by focusing on plans.
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 mentions optional filter by unidade_id and bulk support, but does not explicitly state when to use this tool over alternatives, nor provide any exclusion criteria. Usage is implied but not fully guided.
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.