ask_ai

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It only restates the purpose without revealing whether the operation is read-only, what happens with the query, or how the response is returned. This is a significant gap for a tool that relies on an external AI service.

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 a single sentence of 11 words, front-loaded with the action and target. It is highly concise with no wasted words, and every word contributes to the minimal purpose statement.

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 has no output schema and no annotations, so the description must provide more context. It fails to mention usage guidance, behavioral implications, or any expectation about the AI's response, leaving the agent to guess. Given the simplicity of the tool, this is still a noticeable gap.

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 input schema covers both parameters (orgId, query) with basic descriptions, and the tool description adds no additional meaning. Since schema coverage is 100%, the baseline score of 3 applies; the description does not compensate for any missing parameter context.

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 action ('Ask'), the target ('GitBook AI'), and the scope ('organization's documentation content'). It is distinct from sibling tools that manage spaces, pages, or files, so there is no ambiguity about what this tool does.

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 gives no guidance on when to use this tool versus alternatives such as search_space_content or get_page. It does not mention any prerequisites, exclusions, or context that would help an agent decide between asking the AI and searching content directly.

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