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 and excels. It details critical behavioral traits: the tool 'Always runs in deep mode,' is 'Safe by design: shows detailed preview before deletion, requires explicit confirmation,' works 'cross-platform (Linux, Windows, macOS),' and includes warnings about browser instances preventing cleanup. It also explains the optional 'LIBRARY PRESERVATION' feature and the two-phase confirmation process, providing comprehensive context beyond what the input schema alone would convey.

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 and front-loaded with key information (purpose, critical warning, categories). Every sentence earns its place by providing essential details like platform compatibility, safety design, and workflow. It is appropriately sized for a complex tool but could be slightly more concise by integrating some bullet points into prose, hence a 4 instead of 5.

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?

Given the tool's complexity (system-wide cleanup with safety mechanisms), no annotations, and no output schema, the description is highly complete. It covers purpose, usage guidelines, behavioral traits, parameter context, prerequisites, workflow, and use cases. It effectively compensates for the lack of structured fields, providing all necessary information for an AI agent to invoke the tool correctly and safely.

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, so the baseline is 3. The description adds significant value by explaining parameter semantics in context: it clarifies that 'confirm=false' is for preview and 'confirm=true' for execution, and it details the effect of 'preserve_library=true' ('keep your notebook library.json file while cleaning everything else'). However, it doesn't add syntax or format details beyond the schema, keeping it at a 4 rather than 5.

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: 'Scans entire system for ALL NotebookLM MCP data files across 8 categories' and 'shows categorized preview before deletion.' It uses specific verbs ('scans,' 'shows preview,' 'deletion') and clearly distinguishes this cleanup tool from sibling tools like 'remove_notebook' or 'delete_source' by focusing on system-wide data removal rather than content management.

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: 'Use cases: Clean reinstall, troubleshooting auth issues, removing all traces before uninstall, cleaning old browser sessions and installation data.' It also specifies prerequisites ('Close ALL Chrome/Chromium instances BEFORE running this tool!') and offers a detailed 'RECOMMENDED WORKFLOW' with step-by-step instructions, including when to use alternatives like 'setup_auth' or 're_auth' after cleanup.

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