Skip to main content
Glama

notebook_create

Create a new notebook in NotebookLM to organize research, add sources from URLs/YouTube/Google Drive, and generate AI-powered content like podcasts and infographics.

Instructions

Create a new notebook.

Args: title: Optional title for the notebook

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
titleNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states 'Create a new notebook' which implies a write/mutation operation, but it doesn't mention any behavioral traits such as permissions required, whether creation is idempotent, what happens on failure, or the format of the output (though an output schema exists). This leaves significant gaps for a mutation tool.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is extremely concise and well-structured: a clear purpose statement followed by a brief parameter explanation. Every sentence earns its place with no wasted words, making it easy to parse and understand quickly.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Given the tool's simplicity (one optional parameter) and the presence of an output schema, the description is minimally adequate. However, as a mutation tool with no annotations, it lacks context on behavioral aspects like error handling or prerequisites. The output schema mitigates the need to describe return values, but overall completeness is limited.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The description adds meaningful context for the single parameter 'title' by describing it as 'Optional title for the notebook', which clarifies its purpose beyond the schema's basic type and default. With 0% schema description coverage and only one parameter, this adequately compensates, though it could specify constraints like length or format.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the verb ('Create') and resource ('a new notebook'), making the purpose immediately understandable. However, it doesn't differentiate this tool from other creation tools like 'audio_overview_create', 'data_table_create', or 'flashcards_create' that exist among the sibling tools, which would require specifying what makes a notebook distinct.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines2/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides no guidance on when to use this tool versus alternatives. With multiple creation tools available (e.g., 'notebook_create', 'audio_overview_create', 'quiz_create'), there's no indication of what a 'notebook' is or when it's the appropriate choice over other content types, leaving usage context unclear.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/ran-ai-agency/Notebooklm-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server