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 mentions 'estimated costs' and 'cost analysis including per-node costs and total estimated monthly cost,' which gives some behavioral insight (e.g., it's a read-only analysis tool). However, it lacks details on permissions, rate limits, data freshness, or error handling. For a tool with no annotations, 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 front-loaded with the main purpose, followed by specific details in 'Args' and 'Returns' sections. It uses three concise sentences with no wasted words, making it easy to scan. However, the 'Args' and 'Returns' formatting, while helpful, slightly reduces efficiency compared to a single flowing paragraph.

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 no annotations, no output schema, and low schema coverage (0%), the description does a decent job by explaining the tool's purpose, parameter, and return value. However, it lacks details on behavioral aspects like error cases, authentication needs, or how the analysis is performed (e.g., real-time vs. cached). For a cost analysis tool, this leaves room for improvement in completeness.

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 input schema has 1 parameter with 0% description coverage, so the description must compensate. It adds value by explaining 'cluster_identifier: The cluster label or ID' and noting 'Smart identifier resolution: use cluster label or UUID,' which clarifies the parameter's purpose and acceptable values beyond the schema's basic type. This effectively documents the single parameter, though it could specify format constraints more explicitly.

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: 'Analyze the estimated costs of a Kubernetes cluster.' It specifies the verb ('analyze') and resource ('Kubernetes cluster'), and distinguishes it from generic cost analysis tools like 'analyze_costs' by focusing on Kubernetes clusters. However, it doesn't explicitly differentiate from 'get_cost_analysis' or 'get_cost_breakdown_by_service', which are sibling tools.

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 usage context by mentioning 'Smart identifier resolution: use cluster label or UUID,' which implies when to use this tool (for Kubernetes clusters). However, it doesn't explicitly state when to use this tool versus alternatives like 'analyze_costs' or 'get_cost_analysis', nor does it provide exclusions or prerequisites. The guidance is implied but not comprehensive.

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