ask_notebook

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

With no annotations, the description carries full disclosure burden. It fails to mention response format, latency, permission requirements, or limits on question complexity. The agent cannot infer behavioral traits like whether it returns a single answer or multiple sources.

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 extremely concise (three lines) with no fluff. The first sentence conveys the core purpose, followed by minimal but necessary parameter info. Every part earns its place.

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 simple two-parameter Q&A tool, the description covers the input but omits any mention of output behavior or side effects. The presence of an output schema (though not provided) somewhat mitigates the lack of return value description, but the overall completeness is only adequate.

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 0% description coverage, so the description's brief parameter explanations ('The ID of the notebook', 'The question you want to ask based on the notebook's sources') add basic semantic value. However, they lack detail such as format or example values.

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 a natural language question') and the target ('specific NotebookLM notebook'), leaving little ambiguity. However, it does not explicitly distinguish itself from siblings like 'get_summary' or 'get_source_text', though the action is inherently different.

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 no guidance on when to use this tool versus alternatives. It does not mention context like 'when you need to query the notebook's content' or exclude scenarios (e.g., retrieval tasks better suited for other tools).

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