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

Far exceeds the annotations (which only say readOnlyHint=false, destructiveHint=false, openWorldHint=true). It discloses the cost (2 AI credits from the monthly pool, not the org's own key), the dry-run semantics of the missing confirm flag, exactly what is and isn't charged, and the idempotent re-call pattern. This is precisely the behavioral context an agent needs before invoking a credit-spending mutation.

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 purpose is front-loaded and every clause carries procedural weight, but the credit/confirm rule is restated several times ('nothing runs and nothing is charged,' 'SPENDS AI CREDITS ONLY WITH confirm: true'), which bloats an otherwise dense paragraph.

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?

For a generative, credit-spending tool with no output schema, the description covers cost, approval flow, and scoping of consent well. It could say a little more about what the returned comment looks like or whether results are saved as a draft, but nothing essential to calling it correctly 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 coverage is 60%, and the description heavily compensates for the undocumented confirm parameter by spelling out its quote/charge semantics and the required user-approval protocol. It adds little on text, language, or workspaceId, but several of those are already covered by the schema descriptions.

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 first sentence gives a concrete verb+resource ('Write the first comment to go under a post') and even enumerates the intended content (links, engagement question, hashtags). It is clearly distinct from reply_to_comment or create_comment_to_dm, though it never explicitly names those siblings to steer selection.

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 gives a very explicit call sequence: call first without confirm to get a quote, relay it to the user in your own words, wait for a clear yes, then re-call with identical arguments plus confirm: true, and it clarifies that one approval covers only the approved plan. What it lacks is guidance on choosing this tool over sibling generators like suggest_hashtags or write_caption.

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