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

The description discloses the destructive nature ('Clear all papers') and qualifies the scope with 'in-memory' and 'named', which adds context beyond the tool name. However, it does not mention irreversibility or error handling, and since no annotations exist, the description carries the full burden. Still, it is sufficiently explicit for a simple clear operation.

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, front-loaded with the action, no redundant 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?

For a single-parameter clear operation, the description covers the action, scope, and a relevant use case. The existence of an output schema reduces the need to describe return values. Minor gaps include lack of explicit parameter guidance, but overall it's complete enough.

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 has one parameter (collection) with no description, and the description's 'named reading list' hints at the collection parameter but does not explicitly map it. With 0% schema coverage, the description partially compensates by implying the list name, but it doesn't explain default values or valid inputs.

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 tool's function with a specific verb ('clear') and resource ('all papers from a named in-memory reading list'), which distinguishes it from sibling tools like saved_remove and saved_list.

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 provides a use case ('Useful when restarting a research branch') but does not explicitly contrast with alternatives like saved_remove or mention when not to use it. The context is clear but lacks explicit exclusions.

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