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Morfeu333

NotebookLM MCP Server

by Morfeu333

report_create

Generate reports from NotebookLM notebooks in formats like briefing documents, study guides, or blog posts using selected sources and languages.

Instructions

Generate report. Requires confirm=True after user approval.

Args: notebook_id: Notebook UUID source_ids: Source IDs (default: all) report_format: "Briefing Doc"|"Study Guide"|"Blog Post"|"Create Your Own" custom_prompt: Required for "Create Your Own" language: BCP-47 code (en, es, fr, de, ja) confirm: Must be True after user approval

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
notebook_idYes
source_idsNo
report_formatNoBriefing Doc
custom_promptNo
languageNoen
confirmNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior4/5

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It effectively reveals key behavioral traits: the tool requires user approval (via 'confirm=True'), implies a generation process that might be resource-intensive or irreversible, and hints at a safety mechanism. However, it doesn't disclose rate limits, authentication needs, error conditions, or what happens to existing reports, leaving some 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.

Conciseness4/5

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

The description is appropriately sized and front-loaded: the first sentence states the purpose and key requirement, followed by a structured Args section. Every sentence earns its place by providing essential parameter details. However, the Args formatting is slightly verbose, and the purpose statement could be more specific (e.g., 'Generate a report from notebook sources').

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 (6 parameters, mutation operation, no annotations) and the presence of an output schema (which handles return values), the description is largely complete. It covers purpose, usage guidelines, and parameter semantics thoroughly. The main gap is the lack of behavioral details like side effects or error handling, but the output schema mitigates this for return values. For a tool with this parameter count and no annotations, it does well but isn't exhaustive.

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?

The schema description coverage is 0%, so the description must compensate fully. It adds significant meaning beyond the bare schema: it explains that 'notebook_id' is a UUID, 'source_ids' defaults to all sources, 'report_format' has specific options including 'Create Your Own', 'custom_prompt' is required for that format, 'language' uses BCP-47 codes, and 'confirm' must be True after user approval. This covers all 6 parameters with clear semantics and constraints.

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 report.' It specifies the resource (report) and implies the action (generation). While it doesn't explicitly differentiate from siblings like 'slide_deck_create' or 'infographic_create,' the term 'report' suggests a distinct output format. However, it lacks specificity about what kind of report (e.g., content summary, analysis) or from what data beyond the notebook context.

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. It also implies a workflow step (user approval before invocation), though it doesn't name alternatives or specify when-not-to-use scenarios beyond the confirmation requirement.

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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