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

Annotations already declare readOnlyHint=true and destructiveHint=false. The description adds useful behavioral context by specifying what the returned data contains (file names, sizes, upload dates, text preview), which is especially valuable given there is no output schema. It does not discuss pagination or ordering, but for a simple list tool this is acceptable.

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?

A single well-structured sentence conveys the action, resource, and output contents without any filler. The core purpose is front-loaded, followed by useful details.

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 zero-argument, read-only tool with annotations covering safety, this description is fully sufficient. An agent can confidently invoke the tool and know what to expect in the response, even without an output schema.

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 tool has zero parameters, so there is no parameter ambiguity to resolve. The baseline of 4 applies because the description need not add parameter meaning; nothing is missing.

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 ('List') with a clear resource ('knowledge-base documents backing the website chatbot') and enumerates the returned fields (file names, sizes, upload dates, text preview). This clearly distinguishes it from sibling tools like list_chatbots and upload_chatbot_knowledge.

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 provides clear context for when to use the tool: whenever the knowledge-base documents behind the chatbot need to be listed. It does not explicitly exclude alternatives, but the resource specificity makes the intended use obvious, and no sibling tool overlaps with this exact listing purpose.

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