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. It states the tool retrieves information (implying read-only behavior) and mentions 'Smart identifier resolution,' which adds some context about input flexibility. However, it lacks details on permissions, rate limits, error handling, or what 'detailed information' includes (e.g., format, fields). For a read tool with zero annotation coverage, this is insufficient.

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 structured with a clear purpose statement, a note on identifier resolution, and sections for Args and Returns. It is front-loaded and avoids unnecessary details. However, the 'Args' and 'Returns' sections are somewhat redundant with the schema and could be integrated more seamlessly, slightly affecting efficiency.

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 complexity (3 required parameters, no annotations, no output schema), the description is moderately complete. It covers the purpose, parameters, and return type at a high level but lacks depth: no output details, no error conditions, and minimal behavioral context. It meets the minimum for a read tool but leaves significant gaps for an agent to infer usage.

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%, so the schema provides no parameter details. The description lists the three parameters with brief explanations (e.g., 'cluster label or ID'), adding basic semantics beyond the schema. However, it does not clarify the relationship between parameters (e.g., hierarchical structure) or provide examples, leaving gaps in understanding how to use them effectively.

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 detailed information about a specific node.' It specifies the verb ('Get') and resource ('node'), and mentions 'detailed information' to indicate the output type. However, it does not explicitly differentiate from sibling tools like 'get_kubernetes_cluster' or 'list_kubernetes_nodes', which reduces clarity in context.

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 minimal guidance: it mentions 'Smart identifier resolution' for using labels or UUIDs, which hints at parameter usage, but offers no explicit advice on when to use this tool versus alternatives (e.g., 'list_kubernetes_nodes' for multiple nodes or 'get_kubernetes_cluster' for cluster-level details). There are no prerequisites, exclusions, or comparisons to sibling tools.

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