ask_question

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

With no annotations, the description must fully disclose behavioral traits. It only notes that 'persona' and 'response_length' are cleared if empty, but omits side effects (e.g., state changes), authentication needs, rate limits, or costs. The impact of asking a question on the notebook or account is unclear.

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 well-structured docstring of about 10 lines. It immediately states the purpose, then lists parameters with clear explanations, and finally mentions the return type. Every sentence adds value, and there is no extraneous 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?

Given the complexity (6 parameters, no output schema, no annotations), the description covers inputs adequately but lacks details on return structure beyond 'Dictionary with the answer and citation information'. It does not explain possible errors, response format specifics, or how to interpret citations, which would be helpful for an AI agent.

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?

Despite 0% schema coverage, the description explains all 6 parameters: notebook_id, question, source_ids (comma-separated), conversation_id (thread continuation), persona (descriptive role), and response_length (short/medium/long). It adds semantics missing from the schema, such as format and behavior when empty.

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 begins with a clear statement: 'Ask a question to a NotebookLM notebook and get an AI-generated answer.' It specifies the action (ask), the resource (NotebookLM notebook), and the result (AI-generated answer). This is distinct from sibling tools that perform other operations like listing, creating, or exporting.

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 prerequisites, typical scenarios, or when not to use it. Sibling tools like research_and_import or list_sources are not differentiated, leaving the agent without context for selection.

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