ask_notebook

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

There are no annotations, so the description carries the burden of disclosing behavior. It adds meaningful context by explaining that the tool uses notebook sources as RAG context and produces referenced answers. It does not discuss limitations like out-of-scope questions or citation formatting, but the core behavioral model is transparent.

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 short, front-loaded with the action and resource, and each sentence contributes to understanding the tool. The final sentence about Google infrastructure is slightly low-value but does not meaningfully hurt clarity.

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 full input schema and the presence of an output schema, the description covers the essential context: what question to ask, what context is used, and what kind of answer to expect. Minor gaps remain around when to prefer sibling tools and how source_ids changes grounding, but the definition is adequate for correct invocation.

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?

Schema description coverage is 100%, so all three parameters are already documented in the input schema. The description adds no extra parameter-level meaning, which is acceptable given the baseline for fully covered schemas.

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 names a specific operation ('Ask a question'), a specific resource ('sources in a NotebookLM notebook'), and explains the grounding mechanism (RAG with referenced answers). This is clearly distinct from sibling tools like search_youtube or research_topic, so an agent can easily infer what the 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 clear context for when the tool should be used: when the user wants an answer grounded in notebook sources rather than general web search. It does not explicitly name alternatives or state exclusions, so it stops just short of full alternative-routing guidance.

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