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Studio Generate

studio_generate

Generate audio, video, slide decks, quizzes, flashcards, infographics, data tables, mind maps, and reports from a NotebookLM notebook by name or ID; poll the returned task ID until complete.

Instructions

Start generating a studio artifact. Accepts a notebook name or ID.

Non-blocking: returns immediately with a task_id; poll studio_status(notebook, task_id) until is_complete is true. Exception: mind-map renders synchronously (no task_id) — its node tree is under mind_map (or null), the map's id under mind_map_id.

artifact_type selects the artifact kind (each routes to its own generator):

audio — podcast-style overview (audio_format: deep-dive|brief|critique|debate, audio_length: short|default|long).
video — video overview (video_format: explainer|brief|cinematic|short, style: auto|custom|classic|whiteboard| kawaii|anime|watercolor|retro-print|heritage|paper-craft, style_prompt: free-text custom-style prompt — requires style=custom).
cinematic-video — AI-generated documentary video.
slide-deck — slide deck (deck_format: detailed|presenter, deck_length: default|short).
quiz / flashcards — study aids (quantity: fewer|standard|more, difficulty: easy|medium|hard).
infographic — single-image infographic (orientation: landscape|portrait|square, detail: concise|standard|detailed, style: auto|sketch-note|professional|bento-grid|editorial| instructional|bricks|clay|anime|kawaii|scientific).
data-table — extracted data table.
mind-map — mind map (map_kind: interactive|note-backed).
report — text report (report_format: briefing-doc|study-guide|blog-post|custom).

Each per-kind option is valid ONLY for the kind(s) listed above; passing one to a different artifact_type is a validation error, not a silent no-op. Options default to the standard choice when omitted.

source_ids (optional) scopes generation to specific sources; omit it to use every source. It accepts a real list, a JSON-array string, or a comma-separated string (a source title containing a comma needs the JSON-array or list form). instructions is free-text guidance for kinds that accept it (including mind-map). language (optional) is a language code, e.g. en/ja/zh_Hans.

Input Schema

TableJSON Schema

Name	Required	Description	Default
`style`	No
`detail`	No
`language`	No
`map_kind`	No
`notebook`	Yes
`quantity`	No
`difficulty`	No
`source_ids`	No
`deck_format`	No
`deck_length`	No
`orientation`	No
`audio_format`	No
`audio_length`	No
`instructions`	No
`style_prompt`	No
`video_format`	No
`artifact_type`	Yes
`report_format`	No

Output Schema

TableJSON Schema

Name	Required	Description	Default
No arguments

Schema Changelog

Changes observed during successful MCP inspections.

First observedv0.1.0Oct 15, 2026

TDQS

A4.8/5.0

Behavior5/5

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

With no annotations provided, the description carries the full behavioral burden. It discloses non-blocking async behavior, the task_id return, polling requirements, synchronous mind-map behavior with its return fields, and validation behavior for per-kind options.

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 with a front-loaded summary followed by a bullet-style breakdown of artifact types and their options. Given the large number of parameters and artifact kinds, the length is justified and every sentence adds needed clarity.

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

Completeness5/5

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

Despite having an output schema, the description still covers the key async/sync behavior and return shapes needed to invoke the tool correctly. It also explains validation rules and complex source_ids formats, making it complete for this highly parameterized generation tool.

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

Parameters5/5

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 documents all 18 parameters, including per-kind validity constraints, enum values for each artifact type, source_ids input formats, instructions, and language codes.

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 opens with a specific verb and resource: 'Start generating a studio artifact.' It clearly distinguishes the tool from its siblings by explaining that it returns a task_id for polling via studio_status, with mind-map as a synchronous exception.

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?

It gives clear context for use: start generation, then poll studio_status until is_complete is true, and notes the mind-map exception. It does not explicitly state when not to use this tool or point to other related siblings like studio_download or studio_list.

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