Add missing notebooks word to example links (#674)

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Author: Ololoshechkin

docs/docs/examples/Attachments.md

@@ -1,10 +1,10 @@
 # Attachments
 
 [:material-github: Open on GitHub](
-https://github.com/JetBrains/koog/blob/develop/examples/Attachments.ipynb
+https://github.com/JetBrains/koog/blob/develop/examples/notebooks/Attachments.ipynb
 ){ .md-button .md-button--primary }
 [:material-download: Download .ipynb](
-https://raw.githubusercontent.com/JetBrains/koog/develop/examples/Attachments.ipynb
+https://raw.githubusercontent.com/JetBrains/koog/develop/examples/notebooks/Attachments.ipynb
 ){ .md-button }
 
 ## Setting Up the Environment

docs/docs/examples/Banking.md

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 # Building an AI Banking Assistant with Koog
 
 [:material-github: Open on GitHub](
-https://github.com/JetBrains/koog/blob/develop/examples/Banking.ipynb
+https://github.com/JetBrains/koog/blob/develop/examples/notebooks/Banking.ipynb
 ){ .md-button .md-button--primary }
 [:material-download: Download .ipynb](
-https://raw.githubusercontent.com/JetBrains/koog/develop/examples/Banking.ipynb
+https://raw.githubusercontent.com/JetBrains/koog/develop/examples/notebooks/Banking.ipynb
 ){ .md-button }
 
 In this tutorial we’ll build a small banking assistant using **Koog** agents in Kotlin.

docs/docs/examples/BedrockAgent.md

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 # Building AI Agents with AWS Bedrock and Koog Framework
 
 [:material-github: Open on GitHub](
-https://github.com/JetBrains/koog/blob/develop/examples/BedrockAgent.ipynb
+https://github.com/JetBrains/koog/blob/develop/examples/notebooks/BedrockAgent.ipynb
 ){ .md-button .md-button--primary }
 [:material-download: Download .ipynb](
-https://raw.githubusercontent.com/JetBrains/koog/develop/examples/BedrockAgent.ipynb
+https://raw.githubusercontent.com/JetBrains/koog/develop/examples/notebooks/BedrockAgent.ipynb
 ){ .md-button }
 
 Welcome to this comprehensive guide on creating intelligent AI agents using the Koog framework with AWS Bedrock integration. In this notebook, we'll walk through building a functional agent that can control a simple switch device through natural language commands.

docs/docs/examples/Calculator.md

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 # Building a Tool-Calling Calculator Agent with Koog
 
 [:material-github: Open on GitHub](
-https://github.com/JetBrains/koog/blob/develop/examples/Calculator.ipynb
+https://github.com/JetBrains/koog/blob/develop/examples/notebooks/Calculator.ipynb
 ){ .md-button .md-button--primary }
 [:material-download: Download .ipynb](
-https://raw.githubusercontent.com/JetBrains/koog/develop/examples/Calculator.ipynb
+https://raw.githubusercontent.com/JetBrains/koog/develop/examples/notebooks/Calculator.ipynb
 ){ .md-button }
 
 In this mini-tutorial we’ll build a calculator agent powered by **Koog** tool-calling.

docs/docs/examples/Chess.md

@@ -1,10 +1,10 @@
 # Building an AI Chess Player with Koog Framework
 
 [:material-github: Open on GitHub](
-https://github.com/JetBrains/koog/blob/develop/examples/Chess.ipynb
+https://github.com/JetBrains/koog/blob/develop/examples/notebooks/Chess.ipynb
 ){ .md-button .md-button--primary }
 [:material-download: Download .ipynb](
-https://raw.githubusercontent.com/JetBrains/koog/develop/examples/Chess.ipynb
+https://raw.githubusercontent.com/JetBrains/koog/develop/examples/notebooks/Chess.ipynb
 ){ .md-button }
 
 This tutorial demonstrates how to build an intelligent chess-playing agent using the Koog framework. We'll explore key concepts including tool integration, agent strategies, memory optimization, and interactive AI decision-making.

docs/docs/examples/GoogleMapsMcp.md

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 # Google Maps MCP with Koog: From Zero to Elevation in a Kotlin Notebook
 
 [:material-github: Open on GitHub](
-https://github.com/JetBrains/koog/blob/develop/examples/GoogleMapsMcp.ipynb
+https://github.com/JetBrains/koog/blob/develop/examples/notebooks/GoogleMapsMcp.ipynb
 ){ .md-button .md-button--primary }
 [:material-download: Download .ipynb](
-https://raw.githubusercontent.com/JetBrains/koog/develop/examples/GoogleMapsMcp.ipynb
+https://raw.githubusercontent.com/JetBrains/koog/develop/examples/notebooks/GoogleMapsMcp.ipynb
 ){ .md-button }
 
 In this short, blog-style walkthrough, we’ll connect Koog to a Model Context Protocol (MCP) server for Google Maps. We’ll spin up the server with Docker, discover the available tools, and let an AI agent geocode an address and fetch its elevation — all from a Kotlin Notebook.

docs/docs/examples/Guesser.md

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 # Building a Number‑Guessing Agent with Koog
 
 [:material-github: Open on GitHub](
-https://github.com/JetBrains/koog/blob/develop/examples/Guesser.ipynb
+https://github.com/JetBrains/koog/blob/develop/examples/notebooks/Guesser.ipynb
 ){ .md-button .md-button--primary }
 [:material-download: Download .ipynb](
-https://raw.githubusercontent.com/JetBrains/koog/develop/examples/Guesser.ipynb
+https://raw.githubusercontent.com/JetBrains/koog/develop/examples/notebooks/Guesser.ipynb
 ){ .md-button }
 
 Let’s build a small but fun agent that guesses a number you’re thinking of. We’ll lean on Koog’s tool-calling to ask targeted questions and converge using a classic binary search strategy. The result is an idiomatic Kotlin Notebook that you can drop straight into docs.

docs/docs/examples/Langfuse.md

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 # Tracing Koog Agents to Langfuse with OpenTelemetry
 
 [:material-github: Open on GitHub](
-https://github.com/JetBrains/koog/blob/develop/examples/Langfuse.ipynb
+https://github.com/JetBrains/koog/blob/develop/examples/notebooks/Langfuse.ipynb
 ){ .md-button .md-button--primary }
 [:material-download: Download .ipynb](
-https://raw.githubusercontent.com/JetBrains/koog/develop/examples/Langfuse.ipynb
+https://raw.githubusercontent.com/JetBrains/koog/develop/examples/notebooks/Langfuse.ipynb
 ){ .md-button }
 
 This notebook shows how to export Koog agent traces to your Langfuse instance using OpenTelemetry. You'll set up environment variables, run a simple agent, and then inspect spans and traces in Langfuse.

docs/docs/examples/OpenTelemetry.md

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 # OpenTelemetry with Koog: Tracing your AI agent
 
 [:material-github: Open on GitHub](
-https://github.com/JetBrains/koog/blob/develop/examples/OpenTelemetry.ipynb
+https://github.com/JetBrains/koog/blob/develop/examples/notebooks/OpenTelemetry.ipynb
 ){ .md-button .md-button--primary }
 [:material-download: Download .ipynb](
-https://raw.githubusercontent.com/JetBrains/koog/develop/examples/OpenTelemetry.ipynb
+https://raw.githubusercontent.com/JetBrains/koog/develop/examples/notebooks/OpenTelemetry.ipynb
 ){ .md-button }
 
 This notebook demonstrates how to add OpenTelemetry-based tracing to a Koog AI agent. We will:

docs/docs/examples/PlaywrightMcp.md

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 # Drive the browser with Playwright MCP and Koog
 
 [:material-github: Open on GitHub](
-https://github.com/JetBrains/koog/blob/develop/examples/PlaywrightMcp.ipynb
+https://github.com/JetBrains/koog/blob/develop/examples/notebooks/PlaywrightMcp.ipynb
 ){ .md-button .md-button--primary }
 [:material-download: Download .ipynb](
-https://raw.githubusercontent.com/JetBrains/koog/develop/examples/PlaywrightMcp.ipynb
+https://raw.githubusercontent.com/JetBrains/koog/develop/examples/notebooks/PlaywrightMcp.ipynb
 ){ .md-button }
 
 In this notebook, you'll connect a Koog agent to Playwright's Model Context Protocol (MCP) server and let it drive a real browser to complete a task: open jetbrains.com, accept cookies, and click the AI section in the toolbar.