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sanjeev7e

notebooklm-mcp-rpc

by sanjeev7e

Generate a cinematic video (Veo 3, Ultra-tier only)

generate_cinematic_video

Creates a cinematic documentary-style video from a NotebookLM notebook using Veo 3 AI. Requires a Google AI Ultra subscription.

Instructions

Generate an AI-rendered cinematic documentary-style video using Veo 3. Requires a Google AI Ultra subscription on the authenticated account; without it the call returns a server error. Style options are not supported for cinematic video.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
languageNoOutput language code (e.g. en, ja, zh_Hans).
notebookYesNotebook UUID.
sourceIdsNoRestrict generation to these source IDs.
instructionsNo
Behavior4/5

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

Beyond annotations (readOnlyHint=false, openWorldHint=true), the description adds critical context: the requirement for an Ultra subscription and that missing it causes a server error. It also notes style options are unsupported. This is valuable but doesn't cover output format or side effects.

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?

Two sentences with no fluff. The first sentence states the core purpose; the second adds key constraints. Front-loaded and efficient.

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 complexity (4 parameters, no output schema), the description provides the prerequisite and a limitation but lacks details on output format, expected duration, or error handling. It is adequate but incomplete for a full picture.

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

Parameters2/5

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

The description does not explain any parameters beyond the schema. Schema coverage is 75%, but the description adds no context for how parameters like 'instructions' or 'sourceIds' should be used. Baseline would be higher if coverage were over 80%, but at 75% the lack of parameter guidance is a gap.

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

Purpose5/5

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

The description clearly states the tool generates an 'AI-rendered cinematic documentary-style video' using 'Veo 3', and the title specifies 'Ultra-tier only'. This verb-resource pair is specific and distinguishes it from sibling tools like 'generate_video'.

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

Usage Guidelines4/5

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

The description explicitly states a prerequisite (Google AI Ultra subscription) and a limitation (no style options), which helps the agent decide when to use this tool and avoid errors. However, it does not explicitly compare to alternatives like 'generate_video'.

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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