get_mctl_connection_info

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool retrieves connection information but does not specify what that entails (e.g., whether it returns sensitive data like passwords, if it's a read-only operation, or any rate limits). This leaves significant gaps in understanding the tool's behavior and safety.

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, direct sentence that efficiently conveys the core purpose without any unnecessary words or fluff. It is appropriately sized and front-loaded, making it easy to understand at a glance.

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 lack of annotations and output schema, the description is incomplete for a tool that presumably returns connection information. It does not specify the format or content of the returned data (e.g., JSON structure, key details like URLs or tokens), which is critical for an AI agent to use the tool effectively in a Kubernetes context.

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 zero parameters, and the schema description coverage is 100%, so there is no need for parameter details in the description. The baseline for zero parameters is 4, as the description does not need to compensate for any missing parameter information.

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 action ('Get information') and the resource ('how to connect to the full mctl AI-native Kubernetes platform'), making the purpose understandable. However, it lacks specificity about what type of connection information is provided (e.g., credentials, endpoints, configuration details) and there are no sibling tools to differentiate from, so it cannot achieve 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, such as prerequisites, context, or alternatives. It does not indicate if this is for initial setup, troubleshooting, or ongoing management, leaving usage unclear beyond the basic purpose.

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