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chat_configure

Configure chat settings for NotebookLM notebooks to customize conversation goals, response length, and prompts for tailored AI interactions.

Instructions

Configure notebook chat settings.

Args: notebook_id: Notebook UUID goal: default|learning_guide|custom custom_prompt: Required when goal=custom (max 10000 chars) response_length: default|longer|shorter

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
notebook_idYes
goalNodefault
custom_promptNo
response_lengthNodefault

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Behavior2/5

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 states this is a configuration tool (implying mutation) but doesn't mention permission requirements, whether changes are reversible, rate limits, or what the output contains. For a mutation tool with zero annotation coverage, this is inadequate.

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 with the core purpose. The parameter explanations are organized in a clear Args section, though the formatting could be slightly more polished (e.g., using bullet points). Every sentence adds value.

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

Completeness3/5

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

Given that this is a mutation tool with no annotations but with an output schema (which handles return values), the description is moderately complete. It covers parameters well but lacks behavioral context like permissions or side effects, leaving gaps for safe agent operation.

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 description coverage is 0%, so the description must compensate. It successfully explains all 4 parameters: notebook_id (Notebook UUID), goal (with enum values), custom_prompt (conditionally required with character limit), and response_length (with enum values). This adds substantial meaning beyond the bare schema.

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 verb ('configure') and resource ('notebook chat settings'), making the purpose immediately understandable. However, it doesn't differentiate this tool from its many siblings (like notebook_configure or other notebook-related tools), which would require a 5.

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

Usage Guidelines2/5

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

The description provides no guidance on when to use this tool versus alternatives. While it mentions 'notebook chat settings,' it doesn't explain the context or prerequisites for configuration, nor does it reference any sibling tools for comparison.

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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