list_clusters

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

With no annotations, the description discloses that the tool returns compact summaries by default and full configs when verbose=true. It mentions account_id optionality but lacks details on pagination, rate limits, or authentication. Acceptable but incomplete.

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 paragraphs: first clearly states purpose and default behavior, second lists arguments with concise explanations. No wasted words, efficient and front-loaded.

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 an output schema exists (details unknown), the description explains return value distinction (compact vs verbose). However, with many sibling tools, it omits guidance on how this differs from list_all_clusters, leaving room for confusion.

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 description adds significant meaning beyond the input schema: account_id defaults to env var, verbose=false default, and its use cases. Schema coverage is 0%, so the description compensates well for the 2 parameters.

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 lists AWS Ocean Kubernetes clusters in a Spotinst account, specifying default compact summaries and an option for verbose. It also differentiates from siblings like list_clusters_azure by mentioning AWS Ocean.

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 hints at when to use verbose=true (analyzing, troubleshooting, comparing configs) but does not explicitly state when to use this tool over siblings like list_all_clusters or list_clusters_azure. No when-not-to-use or exclusions provided.

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