adaptive_reject_recommendation

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

No annotations are provided, so the description carries full burden. It discloses a key side effect ('feeds negative signal into the feedback loop for model improvement'), which is helpful. However, it does not state whether the rejection is reversible, what happens to the recommendation afterward (e.g., removed, marked), or any permissions needed. It also implies the recommendation must be 'pending' but does not explicitly state the precondition.

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 sentences long, front-loaded with the main action in the first sentence, and the second sentence provides useful additional context. There is no redundant or irrelevant information.

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 tool is simple with one parameter and no output schema. The description covers what the tool does and the purpose (negative feedback loop). It is largely complete for an agent to use correctly, though it could mention what a successful rejection returns or any error conditions. However, given the simplicity, the description is sufficiently informative.

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 description coverage is 100%, and the parameter description ('The recommendation ID to reject') fully explains the parameter. The tool description adds context that the ID refers to a 'pending layout recommendation,' which adds some meaning beyond just 'recommendation ID,' but it does not substantially enhance the parameter understanding.

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 uses a specific verb ('Rejects') and identifies the exact resource ('pending layout recommendation') and the identifier used ('by ID'). This clearly differentiates it from sibling tools, especially adaptive_accept_recommendation which is the opposite action.

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 implies the usage context by stating the action ('Rejects a pending layout recommendation') but does not explicitly mention alternative tools or when to prefer this over adaptive_accept_recommendation or adaptive_get_recommendation. The when-to-use is clear from the action, but there are no explicit exclusions or comparisons.

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