Doktor MCP Server

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

No annotations are provided, so the description carries the full burden. It discloses that the tool lists states with registered doctors and includes counts, which is useful behavioral context. However, it does not mention potential limitations like rate limits, data freshness, or error conditions, leaving gaps in transparency for a read operation.

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 a single, well-structured sentence that efficiently conveys the tool's purpose and output format. It is front-loaded with the main action and includes no redundant information, making it highly concise and easy to parse.

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 the tool's simplicity (0 parameters, no output schema, no annotations), the description is largely complete. It explains what the tool does and what information it returns. However, without an output schema, it could benefit from more detail on the exact return format (e.g., structure of the list), slightly reducing completeness for agent invocation.

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 tool has 0 parameters with 100% schema description coverage, so the schema fully documents the lack of inputs. The description adds value by clarifying the output includes state names and doctor counts, which is semantic context beyond the empty schema. Since there are no parameters, a baseline of 4 is appropriate as the description compensates with output details.

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 specific action ('List states in Mexico'), the resource ('states with registered doctors on doktor.mx'), and includes a distinguishing detail ('with the total number of doctors in each'). It differentiates from siblings like 'ciudades_disponibles' by focusing on states rather than cities, making the purpose unambiguous and well-specified.

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 implies usage for retrieving state-level doctor statistics, but does not explicitly state when to use this tool versus alternatives like 'ciudades_disponibles' or 'buscar_doctor'. It provides clear context (listing states with doctors) but lacks explicit exclusions or named alternatives, leaving some ambiguity in tool selection.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.