aws_sdk_wrapper

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

No annotations are provided, so the description carries the full burden. It discloses that the tool calls AWS services and returns responses, but lacks details on authentication requirements (beyond profile_name), error handling, rate limits, or side effects. The example adds some context but doesn't fully compensate for the missing behavioral traits.

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 clear sections (Args, Returns, Example), front-loaded purpose, and no redundant sentences. However, it could be more concise by integrating the example more tightly or trimming minor details, but overall it's efficient and easy to parse.

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 high complexity (5 parameters, no output schema, no annotations), the description is incomplete. It explains parameters and provides an example, but lacks details on authentication, error handling, or response formatting. For a generic wrapper with many sibling tools, more guidance on when to use it versus specific tools would enhance completeness.

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 adds significant meaning by explaining each parameter's purpose (e.g., service_name as 'The name of the AWS service to call'), providing examples (e.g., 's3', 'ec2'), and detailing operation_kwargs as 'The arguments to pass to the operation.' This goes beyond the schema's basic titles, though it doesn't cover all possible nuances.

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 as 'A generic AWS SDK wrapper to call any AWS service and operation,' which is specific (verb: 'call,' resource: 'any AWS service and operation') and distinguishes it from sibling tools that are specific to individual services like 'ce-get_cost_and_usage' or 's3-list_buckets.'

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 explicitly provides usage guidance by naming the tool as a 'generic' wrapper for 'any AWS service and operation,' implying it should be used when a specific sibling tool is not available. The example further illustrates this with a call to 'ce' service, which has sibling tools, suggesting alternatives exist for common operations.

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