list_aws_recommendations

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

Annotations already declare readOnlyHint=true and destructiveHint=false, so the safety profile is covered. The description adds useful behavioral detail: recommendations are keyed by commitment type and a type appears only if onboarded and available, which helps agents interpret missing keys. Pagination and response shape are not described, but for a read-only list tool this is acceptable.

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 only two sentences and reasonably compact, but the first sentence is largely product marketing ('Evaluate... optimize cloud costs with PerfectScale for Commitments') and adds little operational value. The more precise 'Returns commitment purchase recommendations...' sentence should be front-loaded.

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?

Without an output schema, the description does a decent job explaining return semantics: keying by commitment type and conditional presence when onboarded. However, it omits how the required managementAccountId parameter is used, says nothing about pagination or result shape, and does not distinguish among the many adjacent AWS commitment and recommendation tools in the sibling list.

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 only 33%, so the description needs to compensate for the undocumented parameters. It does not explain how managementAccountId is used, what X-Tenant-Id means, or how to choose between customerContext and X-Tenant-Id. The phrase 'AWS organization' loosely hints at managementAccountId but does not meaningfully add semantics.

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 that the tool returns commitment purchase recommendations for the AWS organization, keyed by commitment type (`compute`, `database`), and explains conditional presence. It is specific enough to distinguish from generic tools like list_optimization_recommendations, though it does not explicitly differentiate from close AWS siblings such as list_aws_savings_plans or get_aws_recommendation.

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 opening sentence places the tool in a broad workflow: evaluating commitments, planning and automating purchases, and optimizing cloud costs. However, this is more marketing language than concrete selection guidance. It does not explain when to use this tool versus list_aws_planned_purchases, list_aws_reserved_instances, or get_aws_recommendation, nor does it provide exclusions.

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