cloudtrail_lookup_events

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

No annotations are present, so the description must convey behavioral traits. It implies a read-only operation ('look up'), but does not detail rate limits, pagination behavior, or what happens when filters are omitted. The schema partially covers input behavior but not output or side effects.

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 very short (two sentences), front-loads the purpose and filters, and avoids redundancy. Every sentence earns its place.

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 6 optional parameters and no output schema, the description is sufficient but not thorough. It does not explain the return format or default behavior beyond what is in the schema. For a simple read tool, it's adequate but could be more complete.

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 100%, so the description adds minimal value beyond listing optional filters. It mentions 'event name, username, resource type' but these are already in the schema. No additional semantic context is provided.

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 'Look up AWS CloudTrail management events' with specific filters, and mentions the auditing use case. It distinguishes itself among siblings by specifying a unique AWS service not covered by other tools.

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 provides a use case ('auditing who changed what'), but does not explicitly state when to avoid using it or mention alternative tools. Lacks explicit prerequisites or exclusions.

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