vmware-aria

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

With no annotations provided, the description carries the burden of behavioral disclosure. It successfully indicates the return structure (projected days for specific dimensions) and implies read-only nature via 'Predict' and 'Returns'. However, it lacks details on data requirements (how much history needed), error cases, or safety characteristics.

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 efficiently structured with purpose front-loaded, followed by return value specification, then structured Args documentation. Every sentence provides distinct value with no redundancy or filler content.

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?

For a 2-parameter tool with simple types and no output schema, the description adequately covers inputs and expected outputs (projected days per dimension). It meets the minimum viable threshold for complexity, though additional behavioral edge cases would strengthen it further.

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%, requiring the description to compensate fully. The Args section successfully documents both parameters: resource_id includes the expected format (UUID) and typical example (ClusterComputeResource), while target clarifies it is an optional Aria Operations target with default fallback behavior.

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 specific action (Predict) and resource (cluster capacity exhaustion) with scope (based on usage trends). It distinguishes from siblings like get_remaining_capacity by emphasizing the predictive/time-based nature and specific dimensions analyzed (CPU, memory, disk).

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 implies usage context (capacity planning based on trends) but provides no explicit when-to-use guidance or differentiation from similar sibling tools like get_remaining_capacity or get_capacity_overview. No prerequisites or exclusions are mentioned.

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