Vultr MCP

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states the tool is for getting available upgrades (a read operation) and mentions identifier resolution, but doesn't cover important aspects like whether it requires specific permissions, rate limits, error handling, or the format of the returned list. For a tool with zero annotation coverage, this leaves significant gaps in understanding its behavior.

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 and concise, with a clear purpose statement followed by 'Args:' and 'Returns:' sections. Every sentence adds value, such as the smart identifier note, and there's no redundant information. It could be slightly more front-loaded by integrating the return info into the main sentence, but overall it's efficient.

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 moderate complexity (querying upgrades for a cluster), no annotations, no output schema, and low schema coverage, the description is adequate but incomplete. It covers the purpose and parameter semantics well, but lacks details on behavioral aspects like permissions, rate limits, or error cases, which are important for a tool interacting with Kubernetes clusters.

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 description adds meaningful context for the single parameter 'cluster_identifier' by explaining 'Smart identifier resolution: use cluster label or UUID,' which clarifies the expected input format beyond the schema's basic string type. With 0% schema description coverage and only one parameter, this compensation is effective, though it could be more detailed (e.g., examples or constraints).

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's purpose: 'Get available Kubernetes version upgrades for a cluster.' It specifies the verb ('Get') and resource ('available Kubernetes version upgrades for a cluster'), making the action explicit. However, it doesn't explicitly differentiate from sibling tools like 'get_kubernetes_versions' or 'upgrade_kubernetes_cluster', which could be related but serve different purposes.

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 some implied usage context by mentioning 'Smart identifier resolution: use cluster label or UUID,' which suggests when to use this tool—when you need upgrade options for a specific cluster. However, it lacks explicit guidance on when to use this versus alternatives like 'get_kubernetes_versions' (which might list all versions) or 'upgrade_kubernetes_cluster' (which performs the upgrade), and doesn't mention prerequisites or exclusions.

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