list_vngs_azure

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

The description discloses return behavior (compact summaries by default, full configs with verbose) and lists what verbose provides (VM sizes, labels, resource limits). With no annotations provided, the description carries the full burden of transparency and does so adequately. No contradictions are present.

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: four sentences plus an Args list. The purpose is front-loaded, followed by default behavior and verbose explanation. There is no redundancy or wasted text. The structure is clean and easy to parse.

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 complexity (3 parameters, output schema exists), the description covers the main functionality, default output, and parameter details. It does not mention pagination or limits, which might be relevant for a list operation, but the presence of an output schema likely documents return structure. Overall, it is largely complete for typical use cases.

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's explicit 'Args' section is critical. It explains ocean_id, account_id, and verbose, including for verbose a usage hint. The parameter descriptions add meaningful context beyond the schema, though account_id's explanation is somewhat brief ('Account ID for an Azure account'). Overall, it compensates well for the schema's lack of descriptions.

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 'List Azure Ocean Virtual Node Groups', specifying the verb and resource. The 'Azure' qualifier distinguishes it from the sibling tool 'list_vngs', which likely targets a different cloud provider. The purpose is unambiguous and specific.

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 usage guidance for the verbose parameter ('Use when analyzing VNG settings, troubleshooting, or comparing configs'), but it does not explicitly differentiate this tool from sibling tools like 'get_vng_azure' or 'filter_vngs_by_tag'. There is no mention of when to use this tool versus alternatives, leaving potential ambiguity for an AI agent.

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