NanoKVM MCP Server

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively describes the return format (a dictionary with specific fields like connected, width, height), which is helpful. However, it doesn't cover potential errors (e.g., if the device is offline), latency, or side effects (e.g., whether this query impacts system performance). For a read-only tool, this is adequate but lacks depth in operational context.

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 extremely concise and well-structured: the first sentence states the purpose, followed by a clear breakdown of the return values. Every sentence adds value without any fluff or repetition, making it easy to parse and understand quickly.

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 reasonably complete for a status-checking operation. It explains what the tool does and what it returns. However, without annotations or output schema, it could benefit from mentioning error conditions or dependencies (e.g., requires the device to be powered on), leaving some contextual gaps.

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 0 parameters with 100% coverage, so no parameter documentation is needed. The description correctly omits parameter details, focusing instead on the output. This aligns perfectly with the schema, earning a high score as it avoids redundancy and maintains clarity.

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 ('Get HDMI connection status and resolution') and identifies the exact resource (HDMI connection). It distinguishes itself from sibling tools like nanokvm_hdmi_reset (which resets) or nanokvm_screenshot (which captures images), making the purpose unambiguous and well-differentiated.

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 no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites (e.g., device power state), exclusions, or comparisons to siblings like nanokvm_hardware (which might include broader hardware info) or nanokvm_info (which could provide general system status). Without such context, the agent lacks direction on optimal usage scenarios.

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