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

Annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior. The description adds no additional behavioral detail (e.g., pagination, rate limits, error handling), and it is fully consistent with the 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?

Two short sentences with no waste. The core action is front-loaded and the use case is given in the second sentence.

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 read-only list tool with rich annotations and detailed schema descriptions for the key parameters, the description covers the essential purpose. It does not describe the return shape or pagination, but that is partly inferable from the tool name and offset parameter.

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?

The schema provides thorough descriptions for post_id and account_id, but offset is only defined by type/min/max. Schema coverage is 67%, and the tool description adds no parameter-level semantics beyond the schema, leaving offset's purpose implicit.

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-resource pair: list reactions on a LinkedIn post, and gives a practical use case ('engagement analysis or to identify who reacted'). It does not explicitly name sibling tools, but 'people/reactions on a LinkedIn post' distinguishes it from listing comments or reacting to a post.

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 offers clear context for when to use the tool ('Use for engagement analysis or to identify who reacted'). It does not mention when not to use it or point to alternatives like social_list_comment_reactions for comment reactions, but the intended use is explicit.

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