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 retrieves statistics, implying a read-only operation, but doesn't specify whether it requires authentication, has rate limits, returns real-time or historical data, or details the format of the returned information. For a tool with zero annotation coverage, this leaves significant behavioral gaps.

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 a clear purpose statement followed by parameter and return sections. Every sentence adds value: the first defines the tool, the second explains the parameter with examples, and the third outlines the return. There's no redundant or verbose content, making it 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 has one parameter with low schema coverage (0%) but good description compensation, no annotations, and an output schema exists (which handles return values), the description is minimally adequate. It covers the purpose and parameter semantics but lacks behavioral details and usage guidelines, leaving room for improvement in completeness for effective agent use.

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 'instance_id' by explaining it can be an ID, label, or hostname with examples ('web-server', 'db.example.com', or UUID). Since schema description coverage is 0% and there's only one parameter, this compensates well, providing clarity beyond the basic schema type. However, it doesn't cover edge cases or validation rules.

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 bandwidth usage statistics for an instance.' It specifies the verb ('Get') and resource ('bandwidth usage statistics'), and distinguishes it from siblings by focusing on bandwidth metrics rather than other instance attributes. However, it doesn't explicitly differentiate from similar tools like 'get_bare_metal_bandwidth' or 'get_usage' that might also retrieve usage data.

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 no guidance on when to use this tool versus alternatives. It doesn't mention prerequisites, context for selecting this over other bandwidth or usage tools, or any exclusions. The agent must infer usage from the purpose alone, which is insufficient for optimal tool selection.

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