List AI knowledge bases

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

Annotations already declare readOnlyHint=true and openWorldHint=true, so safety is covered structurally. The description adds essentially nothing beyond the [READ] tag and the endpoint path; it does not describe pagination, return shape, or scope.

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 single line is short and front-loaded with the [READ] marker. It is concise, though arguably under-specified rather than deliberately minimal.

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 listing tool with no output schema, the description should at least hint at what is returned or how results are scoped. It provides none of that, leaving the agent without a mental model of the response.

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?

There are zero parameters, so the schema is trivially complete and the description carries no parameter burden. Baseline for a 0-param tool is 4.

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 merely restates the tool name plus an HTTP verb and path ("OpenAPI: GET /knowledge-bases"). It does not explain what an AI knowledge base is or how this list differs from siblings like list_ai_models or list_ai_datasets. The verb+resource is present but adds no semantic value beyond the title.

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?

There is no guidance on when to use this tool versus the many other list_ai_* siblings. An agent gets no help deciding this is the right list to call.

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