Agent Development using Gemini CLI

DOMENDRA — Tue, 03 Mar 2026 18:42:12 +0000

This is a submission for the Built with Google Gemini: Writing Challenge

What I Built with Google Gemini

Technical Deep Dive: Building with the ADK 🛠️
Unlike a standard chatbot, I built an Autonomous Agent using the Gemini ADK. The CLI allowed me to rapidly iterate on the agent's "brain" without leaving my terminal.
The Architecture
The core of the project relies on Function Calling. I defined a set of tools that the Gemini model can decide to invoke based on the user's intent.
Key Snippet: Defining Agent Tools
Here is how I structured a tool within the ADK framework to allow my agent to interact with [External API/Local System]:
The Development Workflow: Gemini CLI
Using the Gemini CLI was a game-changer for my productivity. Instead of jumping between browser tabs, I was able to:
Initialize the project directly with gemini init.
Test Prompts instantly to see how the agent handled complex multi-turn conversations.
Debug Tool Outputs by watching the raw JSON exchanges between the ADK and the model.
Pro Tip: If you're building with the ADK, focus on your System Instructions. I spent 40% of my time refining the "Persona" to ensure the agent didn't "hallucinate" tool arguments that didn't exist.

Why the ADK?
I chose the ADK over a standard REST wrapper because:
State Management: The ADK handles the conversation history and context window efficiently.
Tool Orchestration: It simplifies the "loop" where the model requests a tool, the code executes it, and the result is fed back to the model

Agents Development in the Gemini CLI using Gemini API keys

DOMENDRA — Tue, 03 Mar 2026 18:17:21 +0000

*Technical Deep Dive: Building with the ADK 🛠️
Unlike a standard chatbot, I built an Autonomous Agent using the Gemini ADK. The CLI allowed me to rapidly iterate on the agent's "brain" without leaving my terminal.
The Architecture
The core of the project relies on Function Calling. I defined a set of tools that the Gemini model can decide to invoke based on the user's intent.
Key Snippet: Defining Agent Tools
Here is how I structured a tool within the ADK framework to allow my agent to interact with [External API/Local System]:
The Development Workflow: Gemini CLI
Using the Gemini CLI was a game-changer for my productivity. Instead of jumping between browser tabs, I was able to:
Initialize the project directly with gemini init.
Test Prompts instantly to see how the agent handled complex multi-turn conversations.
Debug Tool Outputs by watching the raw JSON exchanges between the ADK and the model.
Pro Tip: If you're building with the ADK, focus on your System Instructions. I spent 40% of my time refining the "Persona" to ensure the agent didn't "hallucinate" tool arguments that didn't exist.

Why the ADK?

I chose the ADK over a standard REST wrapper because:
State Management: The ADK handles the conversation history and context window efficiently.
Tool Orchestration: It simplifies the "loop" where the model requests a tool, the code executes it, and the result is fed back to the model

Forem: DOMENDRA

Agent Development using Gemini CLI

What I Built with Google Gemini

Agents Development in the Gemini CLI using Gemini API keys

Why the ADK?