K8s Doctor MCP

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 mentions analyzing logs and events to identify root causes and suggest solutions, but does not specify whether this is a read-only operation, requires permissions, has side effects, or details output format. For a diagnostic tool with potential complexity, this leaves significant gaps in understanding its behavior.

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, efficient sentence that front-loads the core purpose without unnecessary words. It could be slightly more structured by separating key actions, but it effectively communicates the tool's intent in a concise manner, earning a high score for brevity and clarity.

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 complexity (diagnosing pods with multiple parameters), lack of annotations, and no output schema, the description is incomplete. It does not address behavioral traits, output format, or usage context, which are critical for an agent to invoke the tool correctly in a server with many sibling tools, leading to significant gaps in contextual understanding.

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 description coverage is 100%, meaning the input schema already documents all parameters (namespace, podName, detailed) with descriptions. The description adds no additional meaning beyond what the schema provides, such as explaining how 'detailed' affects the analysis or the scope of logs included, so it meets the baseline but does not enhance parameter understanding.

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 tool's purpose as analyzing pod status, logs, and events to identify root causes and suggest solutions, which is specific and actionable. However, it does not explicitly distinguish this tool from siblings like 'analyze-logs', 'check-events', or 'full-diagnosis', which likely have overlapping functionalities, so it falls short of a perfect score.

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 such as 'analyze-logs' or 'debug-crashloop'. It lacks explicit context, exclusions, or prerequisites, leaving the agent to infer usage based on the purpose alone, which is insufficient for effective tool selection.

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