linkedin_reply_to_comment

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

Annotations already mark this as non-read-only and non-idempotent, so the description does not need to restate that. It adds a useful behavioral prerequisite (fetch comments first) but does not disclose further behaviors such as reply visibility, error conditions, or authentication needs.

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 two short sentences, starts with the core purpose, and includes only necessary procedural context. No filler or redundancy.

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 simple mutation tool with fully documented parameters and annotations, the description provides the core purpose, the index-addressing mechanism, and the required prerequisite call. It could mention return behavior or error handling, but the description is otherwise sufficient for an agent to invoke the tool correctly.

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%, with all three parameters fully described. The description merely repeats the zero-based index note from the schema and adds the prerequisite to get_post_comments, which is already in the parameter description.

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 action ('Reply to a specific comment on a post') and distinguishes it from sibling tools like linkedin_comment_on_post by emphasizing 'specific comment' and zero-based indexing. This makes the tool's purpose unambiguous.

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 instructs the agent to call linkedin_get_post_comments first to determine the comment order, giving a clear prerequisite and workflow. It does not explicitly mention alternatives or exclusions, but the context is sufficient for when to use it.

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