notebook_query

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

With no annotations, the description carries the full burden. It discloses that the AI analyzes all sources and returns a grounded, cited answer. This is useful behavioral context beyond the schema, though it could mention response format or limitations.

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 only two sentences, front-loaded with the action, and every word earns its place. No unnecessary elaboration.

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 simple two-parameter schema (both well-described) and no output schema, the description adequately covers what the tool does and its output nature (grounded, cited). It could mention that it works across all sources, but this is implied.

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 baseline is 3. The description adds 'in natural language' for query, which aligns with the schema, but does not provide additional meaning beyond what the schema already states.

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 tool's purpose: asking natural language questions to a NotebookLM notebook and receiving grounded, cited answers. It distinguishes itself from sibling tools (e.g., notebook_list, source_add) by explicitly calling it 'the main tool for getting information from your notebooks.'

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 clear context that this tool is for querying notebooks to get answers, but does not explicitly state when not to use it or list alternatives. Given the sibling tools cover other actions, the usage context is clear enough, though exclusions would improve it.

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