EBS CloudWatch Metrics MCP

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions what metrics are returned but lacks critical behavioral details: whether this requires specific AWS permissions, if it queries CloudWatch or another source, potential rate limits, error conditions, or the format/structure of the output. For a tool with 5 parameters and no annotation coverage, this is a significant gap.

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 appropriately sized. It starts with a clear purpose statement, lists key metrics returned, and provides a parameter section with concise explanations. Every sentence adds value without redundancy, and it's front-loaded with the most important information (what the tool does).

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 complexity (5 parameters, no annotations, but with an output schema), the description is moderately complete. It covers parameter semantics well but lacks behavioral context like authentication needs, data sources, or error handling. The presence of an output schema means return values don't need explanation, but other operational aspects are underspecified for a metric querying tool in a cloud environment.

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 beyond the schema, which has 0% description coverage. It explains each parameter's purpose: volume_id for EBS volume identification, start_time/end_time for query range in ISO 8601 format, period for metric collection interval in seconds with a default, and region as optional AWS region. This compensates well for the schema's lack of descriptions, though it doesn't detail constraints like valid period ranges or region formats.

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: calculating advanced performance metrics for EBS volumes, listing specific metrics like I/O utilization, latency, and throughput. It distinguishes from siblings by focusing on comprehensive metrics rather than specific calculations (e.g., calculate_iops) or basic metrics (e.g., get_ebs_metric). However, it doesn't explicitly contrast with all siblings like list_ebs_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?

No explicit guidance on when to use this tool versus alternatives. While the description implies it's for advanced performance metrics, it doesn't specify scenarios where this is preferred over siblings like get_ebs_metric or calculate_iops. There's no mention of prerequisites, such as needing AWS permissions or CloudWatch data availability.

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