notebooklm-mcp

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 describes the tool's behavior: it generates metadata (name, description, tags) automatically, takes approximately 30 seconds, provides consistent quality, and has a fallback mechanism. It mentions the confirmation workflow and shows metadata for review, though it doesn't specify error handling or rate limits beyond the fallback note.

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

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

The description is well-structured with clear sections (When to Use, Workflow, Benefits, Example, Fallback, How to Get a Link), but it's quite lengthy with multiple paragraphs and marketing-style elements ('🚀', '✅'). While informative, some content like the benefits list and detailed account limits could be condensed or moved elsewhere to improve conciseness.

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

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

For a single-parameter tool with no annotations and no output schema, the description provides substantial context: purpose, usage guidelines, workflow, benefits, example, fallback, and URL acquisition instructions. It adequately compensates for the lack of structured metadata, though it doesn't describe the exact return format beyond the example's structure, leaving some ambiguity about the output.

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

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

The input schema has 100% description coverage, with the 'url' parameter clearly documented as 'The NotebookLM notebook URL'. The description adds context about what constitutes a valid URL (NotebookLM share link) and provides instructions on how to obtain one, but doesn't add semantic meaning beyond what the schema already provides. This meets the baseline for high schema coverage.

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

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

The description explicitly states the tool's purpose: 'Automatically generate notebook metadata via NotebookLM' with the specific verb 'generate' and resource 'notebook metadata'. It clearly distinguishes from sibling tools like 'add_notebook' (manual entry) and 'add_source' (different resource). The title 'AUTO-DISCOVERY' reinforces this specific function.

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

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

The description provides explicit guidance on when to use this tool: 'When user provides NotebookLM URL and wants quick/automatic setup', 'User prefers not to manually specify metadata', and 'Default choice for adding notebooks'. It also names the alternative: 'If auto-discovery fails (rare), use add_notebook tool for manual entry', creating clear decision boundaries.

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