list_clusters

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

No annotations provided, so description carries full burden. It states the tool lists clusters with a GPU summary, implying a read operation. However, it doesn't disclose potential costs, pagination, or what exactly 'GPU utilisation summary' entails. Lacks depth in behavioral traits beyond the basic action.

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?

Two sentences: first states purpose, second provides usage guidance. Front-loaded, no redundant words. Efficient and well-structured.

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 no parameters, no output schema, and no annotations, the description covers core functionality and usage boundaries. It mentions the output includes a GPU utilisation summary, which is valuable. Could be more complete by describing output structure, but it's sufficient for a simple list 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?

Tool has zero parameters, so schema coverage is 100%. Baseline score of 4 applies. Description adds no parameter-specific info, but none is needed.

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?

Description clearly states the tool lists all clusters registered in VibOps along with GPU utilisation summary. It distinguishes from sibling tool list_kubectl_contexts by specifying it's for registered clusters, not raw kubeconfig contexts.

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?

Explicitly tells the agent to start with this tool for available clusters or fleet status, and directs to list_kubectl_contexts for raw kubeconfig contexts, including unregistered clusters. Provides clear when-to-use and when-not-to-use guidance with an alternative.

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