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notebooklm_auth_check

Verify Google authentication status for NotebookLM integration with Canvas LMS to enable AI-powered study notebook functionality.

Instructions

Check NotebookLM authentication status.

Returns whether a valid Google authentication session exists. If not authenticated, you'll need to run notebooklm_auth_setup.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior3/5

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

No annotations are provided, so the description carries the full burden. It discloses that the tool returns authentication status and mentions the need for setup if not authenticated, which adds useful context. However, it lacks details on error handling, response format, or any rate limits, leaving behavioral gaps for a tool with no annotation coverage.

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 front-loaded with the main purpose in the first sentence, followed by a concise explanation of the return value and alternative action. Every sentence earns its place with no wasted words, making it highly efficient and well-structured.

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 low complexity (0 parameters, no output schema, no annotations), the description is mostly complete. It covers purpose, usage, and next steps. However, it could improve by specifying the return format (e.g., boolean or structured data) or error cases, but for a simple auth check, it's largely adequate.

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

Parameters4/5

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

The input schema has 0 parameters with 100% coverage, so no parameter documentation is needed. The description does not add parameter information, which is appropriate here. A baseline of 4 is applied as it meets expectations for a tool with no parameters.

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's purpose with a specific verb ('Check') and resource ('NotebookLM authentication status'), and distinguishes it from its sibling notebooklm_auth_setup by indicating the latter is needed if not authenticated. It directly answers what the tool does without being vague or tautological.

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 explicitly states when to use this tool (to check authentication status) and when to use an alternative (run notebooklm_auth_setup if not authenticated). It provides clear context and exclusions, helping the agent choose between these two sibling tools effectively.

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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