get_azure_vm_rightsizing

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

No annotations are provided, so the description carries the full burden. It thoroughly explains the behavior: uses Azure Monitor CPU, joins costs from Cost Management, categorizes VMs (idle, underutilized, bursty), and details the parameters that control the analysis (limit, max_vms_scanned).

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 well-structured with a clear main section, parameter list, and examples. Every sentence adds value, and the key purpose is front-loaded. No redundancy or filler.

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 (Azure VM rightsizing with CPU and cost data) and no output schema, the description fully explains the logic, return categories, parameter effects, and example use cases. It is complete for an agent to understand and invoke correctly.

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 description coverage is 0%, and the description fully compensates by explaining each parameter: subscription_id (none = all subs), lookback_days (default 14), limit (max VMs, highest savings first), max_vms_scanned (cap to avoid hanging). This adds crucial meaning beyond the 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 it finds idle and oversized Azure VMs using CPU metrics and real cost data. It explicitly positions itself as the Azure parallel of nable's idle-EC2 and rightsizing engines, distinguishing it from sibling tools focused on AWS or other clouds.

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 clear when-to-use guidance through examples and explains the actions for idle (deallocate/delete) and underutilized (downsize) VMs. It lacks explicit when-not-to-use or alternative tool mentions, but the context is well-defined.

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