Skip to main content
Glama
DevstackK

Notebooklm-Unofficial-API-MCP

by DevstackK

chat_cancel

Stop an active NotebookLM chat generation. Pass the returned task ID to cancel a detached ask and end its Google session when one exists.

Instructions

Stop a notebook's active chat generation.

conversation_id defaults to the notebook's most-recent session. Pass the task_id returned by chat_start when cancelling a detached ask: the MCP server abandons its local response stream first, then cancels the associated Google session when one exists. An unknown task ID or one belonging to another notebook is rejected.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
task_idNo
notebookYes
conversation_idNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations, the description carries the full burden and does substantial work: it discloses the cancellation ordering (local response stream abandoned first, then the Google session when present) and the task-ID rejection semantics. It stops short of stating idempotency or what happens when no active generation exists, so it is strong but not exhaustive.

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 leading sentence gives the core action before any nuance, and the remaining sentences each add actionable detail rather than padding. The mid-sentence implementation aside about the local response stream is slightly verbose but justified by the ordering it explains.

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?

An output schema exists, so return values need not be described, and the description covers the cancellation path and error conditions adequately. Remaining gaps are minor: no statement of success semantics or idempotency for a repeated cancel.

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, and it does for two of three parameters: conversation_id's default to the most-recent session and task_id's origin in chat_start plus its rejection conditions. The required notebook parameter carries no explanation, leaving a small gap.

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 first sentence states a specific verb and resource ('Stop a notebook's active chat generation'), which immediately separates it from chat_start and chat_status in the sibling list. The follow-up sentences refine the scope by tying behavior to a specific session and task.

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

Usage Guidelines4/5

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

It explicitly states the default for conversation_id and the condition under which task_id should be supplied ('when cancelling a detached ask'), plus the rejection rule for foreign/unknown IDs. It doesn't compare itself against research_cancel or say when the tool is unnecessary, but the primary selection context is covered.

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