In the fast-paced world of software development, every edge counts. We’re constantly seeking tools that not only automate but also intelligently assist us in our coding journey. For me, the Gemini Command Line Interface (CLI) has become one of those indispensable tools. It’s a game-changer, allowing me to harness the power of AI right within my terminal, accelerating everything from debugging to feature implementation.
However, like any powerful tool, there’s a learning curve. When I first started with Gemini CLI, my results were a mixed bag. Some days, it felt like magic; others, like I was speaking a different language. Over time, I’ve honed my approach, uncovering simple yet profound tricks that dramatically improved my output. If you’re leveraging Gemini CLI for your projects, or even just curious about how to make AI coding more efficient, I’m excited to share my top 10 pro tips. These aren’t just theoretical suggestions; they’re the battle-tested strategies that have transformed my daily workflow. Ready to elevate your AI coding? Let’s dive in.
Setting the Stage for Smarter AI Coding
The foundation of effective Gemini CLI usage lies in how you set up your environment and provide initial context. Think of it as preparing a workspace for a highly intelligent assistant – the better organized and informed the space, the better the assistance you’ll receive.
Always Start in Your Project Folder
This might sound basic, but trust me, it’s a non-negotiable step I always follow. Before I even think about running a gemini command, I ensure I’m nestled comfortably inside my project’s root directory. Why is this so crucial? It gives Gemini the precise vantage point of your codebase it needs, ensuring it loads the correct GEMINI.md file and understands the project’s scope. This simple habit prevents unintended context leaks from other files outside your project and saves valuable time by guiding Gemini straight to the relevant code. It’s like inviting your AI assistant directly into the workshop, not just the general office building.
Provide Persistent Context with GEMINI.md
Gemini CLI can’t read your mind, but it can read your documentation. To give it a robust background understanding of your project, create a .gemini folder in your repository and populate it with a GEMINI.md file. I typically use the /init command to kickstart this process, then fill it with vital project details: style guides, target audience, preferred libraries, and even instructions for running tests. Gemini absorbs this information from its very first launch, making every subsequent interaction more informed and accurate.
What’s particularly neat is how dynamic this context can be. If I update my GEMINI.md file with new architectural decisions or coding standards, a quick /memory refresh command brings Gemini up to speed. I then use /memory show to verify it’s taken effect. This ensures your AI assistant’s knowledge base is always current, mirroring the evolution of your project.
Use /memory add for Quick Context Updates
Not every piece of context needs a full GEMINI.md update. For fleeting but important details – a database port number, a temporary API URL, or a recent team decision – the /memory add command is your friend. It’s a faster, more agile way to inject specific details into Gemini’s working memory without having to open and edit a file. For instance, I might use it to store a recent design choice: /memory add "The database port is 123 and we decided to use Boostrap CSS." This keeps the conversation highly relevant and avoids unnecessary back-and-forths, again verifying with /memory show to be sure.
Mastering Your Prompts and Planning
The quality of your AI-generated code directly correlates with the quality of your prompts. Learning to communicate effectively with Gemini is an art, but these tips help turn it into a science.
Craft Clear, Specific Prompts
This is probably the most emphasized piece of advice from Gemini itself, and I couldn’t agree more. Vague prompts are the quickest route to frustration. Asking “help me fix my UI” is like telling a surgeon “fix my body” – it lacks crucial context. Instead, be painstakingly explicit. Break down tasks into digestible steps, specify the desired output format (e.g., TypeScript code), and even instruct Gemini to await your confirmation before making changes. For example:
# Better prompt with context and checklist request When I tap on a chat message, save that portion of the UI as an image. Provide TypeScript code to implement this feature. Create a step-by-step checklist and ask for my approval before editing any files.
This level of detail dramatically improves Gemini’s ability to understand your intent and deliver precisely what you need, saving countless cycles of refinement.
Ask for a Plan Before Changes
For more complex tasks, or when I’m mindful of token usage, I’ve adopted a powerful strategy: asking Gemini to “generate the plan” first. This isn’t just about saving tokens; it’s about control and foresight. Gemini will outline its proposed changes, often as a numbered list of files and modifications. This allows me to review its strategy before any actual code gets touched. If I spot a misinterpretation or a better approach, I can course-correct the plan, saving significant time and potential headaches down the line. It’s like having a blueprint reviewed before construction begins.
Supercharging Your Workflow with Gemini CLI
Beyond basic interactions, Gemini CLI offers features that integrate seamlessly into your developer workflow, transforming your terminal into an even more powerful environment.
Use Shell Mode for Quick Terminal Commands
Ever been in an interactive Gemini session and needed to quickly check a file, list a directory, or run a local script? Shell mode is your answer. By simply pressing ! within the Gemini CLI, you toggle into your local shell. You can then run commands like pwd or ls, and crucially, the output of these commands is fed back into Gemini’s conversation context. This means you can gather information from your local environment and immediately discuss it with Gemini without breaking your flow. Pressing ! again (or Esc) takes you right back into Gemini. It’s a beautifully integrated way to keep your head in the game.
Search the Web with @search
The internet is an ocean of information, and sometimes, your AI needs to cast a wider net. The built-in @search tool allows Gemini to fetch information from the web, bringing external knowledge directly into your conversation. Need to investigate a specific GitHub issue or look up documentation for a library? Just tell Gemini. For example: @search "https://github.com/google-gemini/gemini-cli/". Gemini will fetch the content and use it as context. You can also search by keyword: @search "How to fix 'Cannot find module' error in Node.js?" Often, I just tell the assistant to “search the web,” and it’s smart enough to figure out what I’m looking for, integrating external solutions directly into our problem-solving session.
Define Custom Slash Commands
If you find yourself repeatedly asking Gemini for similar types of responses – perhaps a specific planning template, or a code review structure – custom slash commands are a revelation. You can define these personalized commands by creating a .gemini/commands directory in your project and adding a TOML file for each command, like plan.toml. Inside, you define a description and a prompt template:
description = "Generate a concise plan from requirements"
prompt = """
You are a project planner. Based on the following requirements, generate a numbered plan with deliverables, time estimates and testing tasks. Requirements: {{args}}
"""
Now, a simple /plan "Add user authentication and registration to the TODO app." unleashes your custom workflow, saving you from typing out lengthy prompts every time. It’s a fantastic way to boilerplate common tasks and maintain consistency in your AI interactions.
Use Non-Interactive Mode for Single Questions
Sometimes, you just need a quick, no-fuss answer. Starting a full interactive chat session for a single query can feel like overkill. That’s where the gemini -p command shines. I use it when I need a fast response without the overhead of chat mode. Just pass your question directly with the command, and Gemini delivers a concise answer right back to your terminal. For instance: gemini -p "summarize the main points of gemini.md". It’s perfect for rapid information retrieval or quick confirmations, keeping your workflow incredibly lean.
Your AI Coding Safety Net: Checkpoints
Even with the smartest AI, sometimes things don’t go as planned. Having an “undo” button for your AI-driven changes is crucial, and Gemini CLI provides exactly that.
Enable Checkpoints (My Undo Button!)
This is, hands down, my favorite safety feature. I enable checkpointing in my settings.json file, and it acts like a built-in “save point” or a mini Git commit before Gemini makes any substantial changes to my files. If a new feature breaks something, or an AI-generated refactor introduces unexpected bugs, I don’t panic. I simply use the /restore command to view a list of saved snapshots and effortlessly roll back to a previous, working version of my project files. This feature alone gives me immense confidence to experiment more freely with Gemini, knowing I have a reliable safety net.
Want to see these commands in action and visualize how they streamline my coding process? I’ve put together a video tutorial demonstrating each of these tips. It’s often easier to grasp these concepts when you see them applied in a live environment.
Watch on YouTube: Gemini CLI Tips
Conclusion
The Gemini CLI is undeniably a powerful tool, capable of transforming how we interact with our code. But its true potential isn’t unlocked by merely running commands; it’s unleashed by understanding these nuanced approaches. From meticulously setting up context to leveraging intelligent planning and robust safety features, these tips have been instrumental in making my AI coding faster, more reliable, and significantly more enjoyable. I hope these insights empower you to get the absolute most out of your Gemini CLI experience, pushing the boundaries of what you can achieve right from your terminal.
Cheers!
