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set2374

NotebookLM MCP Server

by set2374

video_overview_create

Create video summaries from NotebookLM research content by selecting visual styles, languages, and focus areas to present findings in explainer or brief formats.

Instructions

Generate video overview. Requires confirm=True after user approval.

Args: notebook_id: Notebook UUID source_ids: Source IDs (default: all) format: explainer|brief visual_style: auto_select|classic|whiteboard|kawaii|anime|watercolor|retro_print|heritage|paper_craft language: BCP-47 code (en, es, fr, de, ja) focus_prompt: Optional focus text confirm: Must be True after user approval

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
notebook_idYes
source_idsNo
formatNoexplainer
visual_styleNoauto_select
languageNoen
focus_promptNo
confirmNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

No annotations are provided, so the description carries the full burden. It mentions the 'confirm' requirement, which hints at a safety or confirmation step, but lacks details on permissions, rate limits, or what happens during generation (e.g., processing time, effects on the notebook). It adds some context but is incomplete for a creation 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 well-structured and front-loaded: the first sentence states the purpose, followed by a usage guideline, then a clear 'Args:' section listing parameters. Every sentence earns its place with no wasted words, making it efficient and easy to parse.

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

Completeness4/5

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

Given the tool's complexity (7 parameters, creation operation) and no annotations, the description does a good job covering purpose, usage, and parameters. However, with an output schema present, it doesn't need to explain return values, but could benefit from more behavioral context (e.g., generation process). It's mostly complete but has minor gaps.

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?

Schema description coverage is 0%, so the description must compensate. It lists all 7 parameters with brief explanations (e.g., 'Notebook UUID', 'Source IDs (default: all)'), adding meaningful semantics beyond the schema. However, it doesn't fully detail enums like 'visual_style' options or elaborate on 'focus_prompt', leaving some gaps.

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 tool's purpose: 'Generate video overview.' It specifies the resource (video overview) and implies creation/generation. However, it doesn't explicitly differentiate from sibling tools like 'slide_deck_create' or 'infographic_create' beyond the output type, missing specific sibling comparison.

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

Usage Guidelines5/5

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

The description provides explicit usage guidelines: 'Requires confirm=True after user approval.' This clearly indicates when to use the tool (after user approval) and includes a prerequisite condition, offering strong guidance for proper invocation.

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

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