Gems are like your own personalized AI chatbots within Gemini, customized versions of the model that retain specific characteristics and preferences you assign. They are designed to solve the “repetitive prompting” problem by allowing you to pre-save contextual information—such as programming language, framework, coding standards, or project goals—so you don’t have to repeat it in every prompt.

Gems streamline your workflow by providing a pre-configured, specialized assistant ready to tackle complex tasks immediately. This shifts your role from a “user” to an “AI manager” who directs a team of specialized AI agents.

Setting Up Your Custom Coding Gem

• Access Gems: When you log into Gemini Advanced, you’ll see a “Gems” section in the left-hand menu.
• Explore Pre-set Gems: Google provides handy pre-set Gems such as “Coding Helper” which serves as a foundational template for code generation and debugging. You can click on these to get a feel for how Gems work.
• Create a Custom Gem:
  • Click on “Manage Gems” from the left-hand menu, then select “create Gem”.
  • Name Your Gem: Give your Gem a descriptive name (e.g., “Python Refactorer” or “React Component Generator”).
  • Provide Instructions (The Four Pillars): The foundation of a well-defined Gem rests on four pillars: Persona, Task, Context, and Format:
    • Persona: Define the Gem’s role, such as a “senior software developer specializing in Python and Django” or “Brick Bin’s friendly and helpful customer support assistant”.
    • Task: Specify its primary function, like “generate, debug, and refactor code according to best practices” or “respond to email inquiries”.
    • Context: Provide rules of engagement and background information. For example, “adhere strictly to the uploaded PEP 8 style guide and project-specific API documentation”. This is where you can also define your target audience or tone of voice.
    • Format: Dictate the structure of the output, for instance, “all code examples must be in clean, copy-paste-friendly Python blocks with clear, inline explanations” or “draft it in the format of an email”.
  • Knowledge Grounding via File Uploads: A critical capability for coding assistants is grounding their knowledge in external, project-specific documents. You can upload files (like PDFs, business information, FAQs, or codebases) directly from your device or reference Google Drive documents. This allows your Gem to become an expert on niche libraries or your team’s coding standards.
  • Test and Refine: As you build your Gem, you can test it in a preview window to see how it responds to prompts. This facilitates rapid, real-time refinement.
  • Utilize Gemini Extensions: You can integrate Gemini extensions (like Google Workspace apps such as Gmail, Drive, Docs, and Maps) into your Gem’s instructions, allowing it to pull information directly from these sources.
• Saving and Using Your Gem: Once you’re happy, click “create” or “save”. Your Gem will appear in the left-hand menu for easy access. When you select it, all the pre-saved instructions are loaded, and you can immediately provide your specific prompt.

Practical Applications Across the Development Lifecycle

Gems can assist throughout the software development lifecycle, from initial code generation to testing and documentation.

Code Generation and Scaffolding

Use the pre-made “Coding Partner” Gem for general code generation.

Create custom Gems to accelerate boilerplate code creation, such as Python classes, React components, Vue.js components, or Django models.

Debugging and Code Analysis

A custom Gem pre-configured with your project’s language and framework context can help correct syntax errors or logical flaws more accurately.

You can feed linearized lists of operations to a Gem for analysis of complex issues like race conditions.

Code Refactoring and Modernization

Create a dedicated “Code Refactor & Reviewer” Gem. By uploading your team’s style guide (e.g., PEP 8 for Python), it can suggest improvements for efficiency, readability, and enforce architectural patterns.

Gems can help modernize legacy codebases by generating comments, identifying code smells, and suggesting translations from older frameworks to modern equivalents. ForrestKnight successfully used Gemini 2.5 Pro to refactor Rust code by removing for loops and cleaning up if statements, noting the “clean code” it produced.

Automated Testing and Quality Assurance

Gems can generate unit test scenarios and complete, runnable test code for specific frameworks like pytest or Jest, including parameterized tests for wide coverage.

Intelligent Code Documentation

A Gem can be tasked with generating detailed documentation, such as JSDoc comments for JavaScript functions or comprehensive docstrings for Python classes. By using explicit format instructions (e.g., ”Task: Re-write this code with inline JSDoc comments for every function. Do not provide a summary.”) you can ensure the desired output.

Advanced Workflows with Gems

• “Team of Agents” Approach: For complex, multi-step tasks, you can chain multiple specialized Gems together. The output of one Gem serves as the input for another, creating a manual AI pipeline. For example, a “Prompt Assistant Gem” refines your goal into an optimized prompt, which is then passed to a “Coding Mentor Gem” to generate the code.
• Project-Specific Grounding: For professional development, leverage the file upload feature to ground Gems in your project’s unique context, including documentation, style guides, API specifications, and source files. This ensures responses are grounded in official sources and minimizes “hallucinations”.