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

Annotations declare readOnlyHint=false, idempotentHint=false, destructiveHint=false, but the description adds substantial unique behavioral context: returns a proposal for organizer review, does not persist changes, and consumes the same cached budget as the web co-writer. This goes well beyond annotations.

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 front-loaded with core purpose, followed by parameter semantics and behavioral caveats. It is efficient, though the single dense paragraph could be slightly clearer with minor formatting.

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 complexity, nested objects, and 50% schema coverage, the description covers purpose, key parameters, behavioral constraints, and a workflow guide resource. It lacks return value details, but no output schema exists, so some expectation setting is missing.

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 50%, so some compensation is needed. The description names four parameters and maps audience/block targets in detail, but it does not fully explain the payload structure or all required fields beyond what the schema provides.

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 suggests edits to a saved web campaign using authorized content and aggregate context, with a specific verb+resource that distinguishes it from publish/save operations. However, it does not explicitly differentiate from siblings like edit_email_campaign or draft_email_response.

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?

It specifies when to use for suggesting edits and explicitly notes it does not save, publish, widen audience, or grant permission, which helps route versus mutation tools. But it lacks explicit when-not-to-use conditions or named alternatives.

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