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 for behavioral disclosure. It mentions the metrics retrieved and the statistical values returned (average, max, min), but doesn't address important behavioral aspects like authentication requirements, rate limits, error conditions, or whether this is a read-only operation versus a calculation that might trigger monitoring costs.

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 begins with the core purpose, explains the calculation method, then provides parameter documentation with examples. Every sentence adds value with no redundant information, and the parameter documentation is clearly separated in an Args section.

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 an output schema (which handles return values) and the description provides good parameter semantics despite 0% schema coverage, the description is reasonably complete. However, for a calculation tool with no annotations, it could better address behavioral aspects like whether this requires specific AWS permissions or has performance implications.

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 description must compensate. It provides clear semantic explanations for all 5 parameters with examples for volume_id, start_time, and end_time, plus default values and optionality for period and region. This adds substantial meaning beyond the bare schema, though it doesn't explain parameter constraints 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 calculates IOPS (I/O operations per second) for EBS volumes, specifying it retrieves VolumeReadOps and VolumeWriteOps metrics to return average, maximum, and minimum IOPS values. This is a specific verb+resource combination that distinguishes it from sibling tools like calculate_throughput or get_ebs_metric.

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 by specifying the metrics it queries (VolumeReadOps, VolumeWriteOps), but doesn't explicitly state when to use this tool versus alternatives like calculate_throughput or get_ebs_metric. There's no guidance on prerequisites, exclusions, or comparative scenarios with sibling tools.

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