notebook_query_start

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

No annotations are present, so the description carries full burden. It discloses that the tool is asynchronous, returns immediately with a query_id, and requires polling. It also explains the timeout behavior. However, it does not mention any side effects or error conditions, which prevents a perfect score.

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: first sentence sets purpose, second provides selection guidance, third describes return, fourth gives workflow, then Args. Every sentence adds value with no 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 async workflow and sibling tools (notebook_query, notebook_query_status), the description fully explains the usage lifecycle. It covers when to use, what it returns, and how to get results. No gaps for an agent to infer.

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 coverage is 0%, so the description must compensate. It explains each parameter's purpose and defaults (e.g., source_ids default 'all', timeout default from env or 120.0). This adds significant meaning beyond the bare schema types.

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 it starts an asynchronous query for large notebooks that may timeout. It explicitly distinguishes itself from the sibling tool notebook_query by specifying the condition (many sources, >60s). The verb 'start' and resource 'notebook query' are specific.

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 says 'Use this instead of notebook_query when querying notebooks with many sources (50+) where the response may take longer than 60 seconds.' It also provides a clear workflow: start -> poll status. This gives excellent guidance on when and how to use.

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