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

Annotations already establish that the operation is read-only and non-destructive, so the bar is lower. The description adds useful behavioral context by noting that the comment is AI-generated and aimed at building rapport. It does not disclose, however, whether the tool returns the comment text for approval or directly submits it, which is material for an agent.

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?

Three dense sentences, with the core purpose stated first. Every sentence contributes: what it generates, what inputs it uses, and when to use it. No filler or redundant restatement of the tool name.

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?

The description covers purpose, input context, and usage timing, and annotations cover safety. However, there is no output schema, and the description does not state the return value (e.g., a crafted comment string) or clarify that this tool only generates the comment and does not post it. Given the empty schema, an agent could be unsure how to call it or what to do with the result.

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?

There are zero parameters in the schema, so the baseline is 4. The description adds conceptual meaning by naming the inputs the agent should make available: post content, lead context, and campaign context. It cannot score higher because the actual schema has no parameter fields, leaving how to pass these inputs unspecified.

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 states a specific verb and resource: 'Generate a relevant comment for a LinkedIn post.' It clearly communicates the tool's function and implies it is a drafting/generation tool rather than a posting action. It does not explicitly name or differentiate from sibling tools like campaignstack_comment_on_post or campaignstack_reply_to_comment, so it stops short of a 5.

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 gives a clear context for use: 'engaging with a lead's LinkedIn posts before or after connecting.' This tells the agent when the tool is appropriate. It lacks explicit when-not-to-use guidance or mentions of alternatives, such as using comment_on_post when the intent is to publish the comment.

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