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

With no annotations provided, the description carries the full burden of behavioral disclosure. It mentions authentication requirements and quota considerations for source extraction, which adds useful context. However, it doesn't describe what the tool returns (answer format, error behavior), session management implications, or performance characteristics beyond the 1-2 second note about source extraction.

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 poorly structured and contains significant waste. It leads with a header that doesn't explain the tool's purpose, includes extensive setup instructions that belong in documentation rather than a tool description, and buries the actual tool context. Multiple sentences (like the entire 'No Active Notebook' section) don't help an AI agent understand how to invoke this specific tool.

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 complex tool with 7 parameters, nested objects, no output schema, and no annotations, the description is incomplete. It fails to explain what the tool returns, how sessions work, error conditions, or the relationship between notebook_id and notebook_url parameters. The focus on setup and authentication overshadows the tool's actual behavior and output.

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 the schema already documents all 7 parameters thoroughly. The description adds no parameter-specific information beyond what's in the schema. The baseline score of 3 reflects adequate coverage through the schema alone, but the description contributes zero additional parameter semantics.

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 fails to clearly state what the tool does. While the title 'ask_question' suggests asking questions, the description focuses on setup instructions, authentication tips, and library management guidance rather than explaining the tool's core function. It mentions 'conversational research partner' but doesn't specify that this tool actually submits questions to NotebookLM and returns answers.

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 about when to use this tool by explaining prerequisites (needs an active notebook) and referencing sibling tools for setup (add_notebook, list_notebooks, select_notebook). It also includes authentication guidance. However, it doesn't explicitly state when NOT to use this tool versus alternatives like search_notebooks or generate_content.

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