notebook_query_start

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

Without annotations, the description carries the burden of behavioral disclosure. It explains the async behavior, immediate return of query_id, and default timeout. It does not mention side effects, error handling, or authentication, but the core behavioral traits are sufficiently covered.

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 concise and well-structured: a clear purpose statement, when-to-use guidance, a workflow summary, and a parameter list. Every sentence adds value without redundancy.

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 tool's moderate complexity and the presence of an output schema (implied by 'returns immediately with a query_id'), the description provides sufficient context to use the tool correctly, including the complete workflow and parameter details.

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?

Although schema coverage is 0%, the description includes an Args section that explains each parameter with default values and context (e.g., 'source_ids: Source IDs to query (default: all)', 'timeout: Request timeout in seconds (default: from env NOTEBOOKLM_QUERY_TIMEOUT or 120.0)'). This adds meaning beyond the parameter names.

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: 'Start a notebook query asynchronously for large notebooks that may timeout.' It specifies the verb 'start' and the resource 'notebook query', and distinguishes itself from the sibling tool 'notebook_query' by noting the async nature and use case for large 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 explicitly provides when to use this tool vs. the sibling 'notebook_query': 'Use this instead of notebook_query when querying notebooks with many sources (50+) where the response may take longer than 60 seconds.' It also outlines the workflow: 'notebook_query_start -> poll notebook_query_status until completed.'

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