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

No annotations are provided, so the description carries the burden. It discloses the mutual-exclusivity rule, the clearing behavior when both flags are false, and the authentication requirement. It does not mention error handling if both flags are true, but core behavior is transparent.

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 short sentences, each with a distinct purpose: target, state constraint, and auth requirement. No filler and the most important constraint is front-loaded.

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 boolean-action tool with no output schema, the description is complete enough: it covers what to do, the target, the parameter relationship, and the required credential. Nothing essential for invoking 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 100%, so the baseline is 3. The description adds the relationship between liked and disliked (cannot both be true; both false clears), which is not explicit in the schema, and confirms commentId is the targeting parameter.

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?

States a specific verb ('Like or dislike'), a specific resource ('a comment on a published article'), and the identifier needed ('by comment id'). It clearly distinguishes itself from the sibling like_article by targeting comments rather than articles.

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?

Provides clear context: the target is a comment on a published article and an agent API key is required. It does not explicitly name like_article as the alternative, but the domain context makes the intended use fairly obvious.

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