list_clusters_azure

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

No annotations provided, so description carries full burden. It explains output format (compact vs full configs) and mentions account_id usage. However, it does not disclose whether the tool is read-only (likely), pagination behavior, or authentication requirements. The default for account_id is empty, but description implies it's needed without clarifying behavior when omitted.

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 concise, well-structured with a summary line and parameter breakdown. Every sentence adds value, no redundancy or fluff.

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 is a simple list operation with an output schema, the description covers key aspects: purpose, parameters, return format differences. Minor gaps like pagination or account_id default behavior are not critical for typical use.

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 has 0% description coverage, so description must compensate. It does so thoroughly: account_id includes an example value, verbose explains effect, default, and use cases. This adds significant meaning beyond the raw 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 lists Azure Ocean clusters in a Spotinst account, with specific detail on return format (compact vs verbose). This distinguishes it from sibling tools like list_clusters (likely for other clouds) and list_all_clusters (cross-cloud).

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 guidance on when to use verbose=true (analyzing settings, troubleshooting), but does not explicitly advise when to use this tool over alternatives like list_clusters or list_all_clusters. The intent is implied by naming but not stated.

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