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

Annotations already declare readOnly, idempotent, non-destructive, so the safety profile is covered. The description adds real context beyond them: it explains the scope of returned data and that feature preview output is kept separate from the lambda's visitors, which is a non-obvious behavioral detail.

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?

Two sentences, front-loaded with the payload description before the usage cues, and no filler. The phrasing is somewhat wordy ('what a deployed lambda has been doing') but each clause carries information.

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?

With no output schema, the description does the work of explaining what comes back (requests, prints, errors, traffic), and it covers the feature-preview mode. Only minor gaps remain, such as pagination/cursor behavior, which the schema partially handles.

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 100%, so level, limit, since, and feature are already documented in the schema; baseline is 3. The description adds the semantic point that feature output is 'kept apart from the lambda's visitors,' which slightly clarifies the feature parameter, but no extra syntax or default detail is supplied.

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?

States a specific verb and resource and enumerates what the logs contain: requests and responses, prints, errors with stack traces, and traffic volume. An agent can tell this is a log-reading tool rather than a metadata reader, though it never names the nearest sibling (read_lambda) to sharpen the distinction.

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?

Gives concrete triggers: 'Call it after deploying to see that it works, and first when something is reported broken.' That is clear when-to-use guidance, but there is no explicit when-not or named alternative (e.g., read_lambda for status/health).

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