OpenShift 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 describes the tool's scope ('fast, high-level summary'), data sources ('Kubelet API'), and conditional behavior based on the node parameter. However, it doesn't mention performance characteristics beyond 'fast', error handling, authentication requirements, or rate limits that would be important for operational tools.

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 perfectly structured and concise: four sentences that each earn their place. The first establishes purpose and priority, the second adds technical detail, and the final two sentences provide essential parameter guidance with zero wasted words.

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 has an output schema (which handles return values), no annotations, and a simple single parameter, the description provides excellent context about when to use the tool and how parameters affect behavior. The only minor gap is lack of information about error conditions or operational constraints that would be helpful for a cluster monitoring tool.

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 schema has 0% description coverage for its single parameter, but the description fully compensates by explaining exactly what the 'node' parameter does and the behavioral difference between providing it versus not providing it. This adds crucial semantic meaning beyond the bare schema.

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 with specific verbs ('get', 'checks', 'analyzes') and resources ('storage usage for all nodes or a specific node', 'quotas and reported usage from the Kubelet API'). It distinguishes from siblings by focusing specifically on storage reports rather than GPU health, pod diagnostics, or other cluster metrics.

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 explicit usage guidance: 'Use this FIRST' establishes priority, and it clearly explains when to use specific parameter values ('If 'node' is provided, analyzes only that node. If 'node' is not provided, analyzes all worker nodes'). This gives clear context for parameter decisions.

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