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Robiton
by Robiton

save_auth_tokens

Save NotebookLM authentication tokens using cookies from Chrome DevTools when the automated CLI login fails.

Instructions

Save NotebookLM cookies (FALLBACK method - try nlm login first!).

IMPORTANT FOR AI ASSISTANTS:

  • First, run nlm login via Bash/terminal (automated, preferred)

  • Only use this tool if the automated CLI fails

Args: cookies: Cookie header from Chrome DevTools (only needed if CLI fails) csrf_token: Deprecated - auto-extracted session_id: Deprecated - auto-extracted request_body: Optional - contains CSRF if extracting manually request_url: Optional - contains session ID if extracting manually

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
cookiesYes
csrf_tokenNo
session_idNo
request_bodyNo
request_urlNo

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, the description carries full burden. It discloses fallback nature, deprecated parameters, and auto-extraction. However, does not explicitly state whether it overwrites tokens or other side effects.

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?

Well-structured with sections. Slightly verbose but each sentence adds value. Front-loads purpose and critical usage instruction.

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?

Covers purpose, when to use, and parameter meanings. Missing output schema details but acceptable for a token-saving tool with expected simple output.

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?

Schema coverage is 0%, so description adds needed meaning. Each parameter has a brief explanation (e.g., deprecated, auto-extracted, optional). Adds value beyond raw schema.

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?

Clearly states it saves NotebookLM cookies as a fallback method, with a specific verb and resource. Distinguishes itself from siblings by referencing the preferred CLI method 'nlm login'.

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?

Explicitly instructs to use 'nlm login' first and only fall back to this tool if that fails. Provides clear when-to-use and when-not-to-use guidance.

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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