EBS CloudWatch Metrics MCP

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

With no annotations provided, the description carries full burden. It discloses that the tool returns statistical data and mentions default values for 'period' and optional 'region', which adds useful behavioral context. However, it doesn't cover important aspects like authentication requirements, rate limits, error conditions, or pagination behavior for potentially large datasets.

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 with a clear purpose statement followed by detailed parameter documentation. It's appropriately sized for a 7-parameter tool. The only minor inefficiency is the repetition of '조회' (query/retrieve) in both the purpose statement and parameter descriptions, but overall it's front-loaded and each sentence adds value.

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 tool with 7 parameters, no annotations, but with an output schema present, the description provides good coverage. The parameter documentation is comprehensive, and the existence of an output schema means the description doesn't need to explain return values. It could improve by mentioning authentication or error handling, but given the output schema handles return structure, this is reasonably complete.

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?

Given 0% schema description coverage, the description fully compensates by providing detailed parameter documentation in the Args section. It explains each parameter's purpose, lists all supported metric names with specific examples, specifies format requirements (ISO 8601 for timestamps), indicates defaults (period: 300), and notes optional parameters. This adds substantial value beyond the bare schema.

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: '특정 EBS CloudWatch 지표를 조회합니다' (retrieves specific EBS CloudWatch metrics). It specifies the verb (retrieve/query) and resource (EBS CloudWatch metrics), and distinguishes from siblings like 'list_ebs_metrics' (which likely lists available metrics rather than retrieving data) and 'get_advanced_metrics' (which suggests more complex metrics).

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 by mentioning EBS volumes and CloudWatch metrics, but doesn't explicitly state when to use this tool versus alternatives like 'get_advanced_metrics' or 'calculate_iops'. It provides the supported metric names which helps identify appropriate use cases, but lacks explicit guidance on tool selection among siblings.

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