get_notebook_outline

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

While no annotations are provided, the description adds context by labeling the tool as legacy and narrower. However, it lacks details on what the outline contains, side effects, or specific behavior beyond the name.

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?

Two sentences, no wasted words. Front-loaded with 'LEGACY' and immediately states purpose, then provides usage preference. Highly efficient.

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?

With an output schema present (though not shown), return value explanation is not required. The description covers purpose and usage context. Missing parameter description is a minor gap, but overall complete for a simple, legacy tool.

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 0% and the description does not explain the 'path' parameter. Despite the parameter name being intuitive, the description adds no semantic value beyond the schema.

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?

Clearly states the tool gets the notebook's section outline and marks itself as legacy. Distinguishes from read_notebook by describing it as older/narrower workflow.

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?

Explicitly recommends preferring read_notebook() unless the legacy/narrower workflow is needed, providing clear when-to-use and when-not-to-use guidance.

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