get_ecs_rightsizing_recommendations

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

No annotations exist, so the description must cover behavioral traits. It explains the methodology (Container Insights metric, threshold), requirement, and cost implication. However, it does not disclose permissions needed, rate limits, or what the exact output format looks like (missing since no output schema). This is adequate but not comprehensive.

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 tightly written: one sentence for purpose, then methodology, requirement, args with defaults, and examples. No filler. The key information is front-loaded, and every sentence serves a purpose.

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 simplicity (2 parameters, no output schema, no annotations), the description covers all essential aspects: purpose, prerequisites, parameter details, and usage examples. It provides sufficient context for an AI agent to select and invoke the tool correctly.

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 coverage is 0% (no property descriptions in schema), so the description fully compensates. It explains cpu_threshold as 'Flag services with average CPU below this % (default 20%)' and regions as 'AWS regions to scan. Defaults to all opted-in regions.' This adds significant meaning beyond the schema's type/default.

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 opens with a clear action: 'Find ECS Fargate services with over-provisioned CPU allocations.' It specifies the resource (ECS Fargate), the metric (CpuUtilized), and the outcome (downsizing candidates). This distinguishes it from sibling tools like get_rds_rightsizing_recommendations or the generic get_rightsizing_recommendations.

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 states a prerequisite ('Requires Container Insights to be enabled on the ECS cluster') and gives example queries. It does not explicitly mention when not to use this tool or suggest alternatives, but its specificity about ECS Fargate implies its context adequately.

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