list_clusters_azure

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

With no annotations provided, the description bears full responsibility for behavioral traits. It explains the default compact return and the effect of setting verbose=true, disclosing what the agent can expect. It does not mention destructive actions or auth, but as a read-only list operation, this is acceptable.

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 remarkably concise, starting with a clear one-sentence purpose, then explaining output variants, and using a bulleted list for arguments. Every sentence adds value with no redundancy.

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's low complexity (2 optional parameters, no nesting, output schema present) and the server's context, the description covers the core functionality and parameter usage. It does not discuss error handling or pagination, but that is acceptable for a straightforward list operation.

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 input schema has 0% description coverage, so the description must compensate. It offers a concrete example for account_id (act-9785011e) and explains the verbose parameter's purpose and use cases, adding substantial meaning beyond the schema's mere type and default.

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, specifically mentioning its scope (in a Spotinst account) and distinguishing between compact and verbose outputs. Among siblings like list_clusters and list_all_clusters, this tool's Azure-specific focus is unambiguous.

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 the verbose parameter (e.g., analyzing settings, troubleshooting). While it does not explicitly exclude alternatives, the context of sibling tool names (e.g., list_clusters_azure vs. list_clusters) makes the Azure-specific purpose clear, and the usage tips for verbose are helpful.

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