export_artifact

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

No annotations are provided, so the description carries full burden for behavioral transparency. It states the tool creates a new Google Doc/Sheet and returns its URL, but does not disclose whether the original artifact is modified (likely not), required permissions, or potential side effects. The tone is generally clear, but more detail on what happens to the artifact could improve transparency.

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 one-sentence summary followed by a bullet list of supported conversions and a clear args section. Every sentence adds value without redundancy, and the most important information (the core action) is front-loaded.

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 complexity (4 parameters, no annotations, but with an output schema indicated), the description adequately covers the basic usage and return type. However, it lacks information on error handling, validation (e.g., ensuring export_type matches artifact type), and prerequisites (e.g., authentication). This could lead to incomplete understanding for an AI agent.

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?

The input schema has 0% description coverage, so the description must compensate. It lists all four parameters with brief but clear explanations: notebook_id ('Notebook UUID'), artifact_id ('Artifact UUID to export'), export_type ('docs or sheets'), and title ('Title for exported document (optional)'). This adds meaningful context beyond the raw schema, though it could be more detailed (e.g., how to obtain UUIDs).

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 exports a NotebookLM artifact to Google Docs or Sheets, specifying the mapping of artifact types to export targets (Data Tables to Sheets, Reports to Docs). It distinguishes itself from the sibling tool 'download_artifact' by specifying the target format (Google Doc/Sheet vs likely file download).

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 for when to use this tool: to create a Google Doc or Sheet from an artifact. It implies use over 'download_artifact' when the user needs a collaborative document. However, it does not explicitly state when not to use it or mention prerequisites like authentication or required artifact types.

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