DEV Community: Srujana Maddula

Using Amp (AI) For Static Code Analysis

Srujana Maddula — Thu, 20 Nov 2025 14:41:18 +0000

AI-powered software tools have completely changed how we write code. Most developers today use at least one AI coding tool, and many swear by their favorite. But after trying several—Cursor, Copilot, and now Amp—I’ve learned that not all tools perform the same.

In this article, I’ll share my experience with Amp for static code analysis, explain why it stands out, and walk you through how to use it step by step.

What issues does static code analysis detect?

Static code analysis focuses on identifying code quality issues and security vulnerabilities. Here are some common ones it catches:

Code duplication

Copy-pasted code is a maintenance nightmare. If a bug or necessary update is discovered in one instance, developers must track down and fix every occurrence. Static analysis helps flag these and convert them into reusable functions.

SQL injection

SQL injection happens when a program inserts user input directly into an SQL query without proper validation or parameterization.

Attackers can then alter the query and access or modify sensitive data. Static code analysis identifies such common patterns and offers potential fixes.

Styling issues

Static code analysis can identify inconsistent indentation, weird naming, and mixed styles that make the code harder to read and maintain.

Performance optimizations

Static code analysis tools can detect inefficient or redundant logic that slows down execution, such as unnecessary loops, memory leaks, inefficient data structures or algorithms, and unoptimized recursive calls.

Why Use Amp for static code analysis?

Unconstrained token usage: Unlike many AI tools, Amp doesn’t limit the number of tokens per task. It automatically selects the best model for the task, delivering high-quality code without running into context limits.

Collaboration: There’s a share button that lets you share the Amp threads with your colleagues. You can also create a workspace and add your teammates. All workspace threads are visible to members by default, but you can adjust permissions to control access.

Flexible setup: Amp offers both an IDE extension and a CLI tool. If you prefer working with commands, you can run Amp directly from your terminal. It’s VS Code extension also feels natural in the IDE setup.

Integration compatibility: In addition to native IDE integration, the Amp SDK lets you stream inputs and outputs between your custom applications and Amp. That means you can use it to programmatically build AI workflows and integrate Amp into your custom development tools.

Different ways Amp can perform static code analysis

Amp in IDE

Amp provides native extensions for VS Code, JetBrains, Cursor, and other popular IDEs. Once installed, it appears as a chat window inside your IDE, where you can ask questions, assign tasks, switch between different Amp modes, and get intelligent code assistance.

Amp continuously runs in the background, analyzing your code and identifying quality issues in real-time. You can open the Amp chat window in your preferred IDE and ask it to analyze specific code sections for security vulnerabilities or check files for code quality issues.

Over time, Amp learns from your codebase and developer patterns and provides more accurate, context-aware solutions.

Amp as CLI

Amp is also available as a command-line interface. You can install it using a curl command directly from your terminal and interact with it through simple prompts.
Its interactive mode lets you chat with Amp in your terminal, while the -x command activates execute mode, where Amp internally performs tasks step by step and displays the final output.

When you navigate to your project directory, Amp reads the code context and relevant files from the terminal. However, unlike the IDE version, the Amp CLI doesn’t automatically run in the background. You need to explicitly prompt it to perform static code analysis when required.

Amp in CI/CD

You can integrate Amp into your CI/CD pipeline to perform code quality checks automatically with every push. For example, in GitHub Actions, create a yaml file inside .github/workflows/file_name.ymland add instructions to run Amp after each commit or push.

You can also include SARIF files so that Amp’s suggestions appear directly in the Security tab and inline within pull requests on GitHub.

How to use Amp for static code analysis?

The easiest way to use Amp is through VS Code, and that’s what most developers prefer. Once installed, you can start scanning and fixing code directly inside your IDE.

To get Amp installed and running on your VS Code, follow this guide.

After the setup, you’ll see the Amp chat interface appear on the left sidebar of your IDE.

Open any file you want to analyze. I started with a Python file named retriever.py and prompted, “Scan this file for code quality issues.”

Amp quickly highlighted the line numbers with exact issues and categorized them into high, medium, and low priorities. For example, syntax errors and network failures appeared under high priority since the code doesn’t run with these issues. Similarly, less severe problems were placed under the medium and low priority categories.

Next, I asked it to find possible bugs in the file. Amp detected missing error handling cases, empty list possibilities, unused parameters, and more.

I also had a SQL script in the same repository, so I asked Amp to check for SQL injection vulnerabilities. Since the code was secure, it confirmed there were none.

Not only can Amp identify static code issues, but you can also prompt it to fix them automatically. The tool applies the fixes directly in your IDE and updates the code once you accept its suggestions.

Conclusion

Using Amp for static code analysis brings powerful security checks and real-time assistance to your development workflow in today’s AI-driven world. By catching code quality issues and security vulnerabilities right inside the IDE, Amp helps you maintain best coding practices and minimize issues in later stages of the development lifecycle.

As AI continues to reshape software development, organizations that combine AI productivity with robust coding practices will have a significant competitive advantage. Start using Amp in your coding workflow today to build more quality and secure software.

Generate Docs with Amp Code

Srujana Maddula — Fri, 03 Oct 2025 13:26:01 +0000

When you have a quick, one-off task, you don’t need to start a whole chat thread. Instead, you can run Amp CLI commands directly. Ask once, get your result, and you’re done. For example, let’s look at how to use the -x command to generate project documentation.

What is Amp CLI?

Amp CLI is an interactive console. It’s how you chat with a chatbot but in a terminal interface. When you start a session, Amp listens to your commands, returns results, and keeps track of the conversation context for follow-up questions.

It’s like opening a chat window right in your terminal. Since Amp keeps the thread alive, you build on top of prior answers.

Sometimes you don’t need a full chatbot thread; you just want to run a single command, get the result, and immediately close the session. For this, we have the --execute command.

Amp `--execute` command

Once you’re logged in to Amp through your terminal, you can run:

amp -x "your prompt"

In this mode, Amp processes your prompt once, performs the task, and immediately closes the session.

Using Amp to generate project documentation

Let’s ask Amp to create documentation.

Inside the project repo, run the following prompt:

amp -x "create a README.md with installation and usage instructions"

Now, run cat readme.md. It opens a README.md file as follows:

You can also create release notes using Amp code. You can either prompt directly as shown above, or create a bootstrap/text file with detailed instructions and execute it using the -x command.

Since you already know how to prompt directly, I’ll show you the bootstrap method.

First, save the following instructions in a text file. I’ll save it as release-notes.prompt.txt

Task: Create RELEASE_NOTES.md for non-technical readers.

Source: Summarize the following changelog content.

Include:
- What’s new in plain English.
- Impact, risks, rollback summary.
- Upgrade checklist.

Now run the below command:

amp -x "$(cat release-notes.prompt.txt)" > RELEASE_NOTES.md

As instructed in the text file, this generates a RELEASE_NOTES.md file and populates it with the latest release changes using the changelog.

Conclusion

When you have a set of pre-defined tasks or you have a one-time task, you can easily execute them using the -x command. You can also integrate -x commands into Git hooks or CI/CD pipelines so that it performs the set instructions on every commit, tag, or release.

For example, you could set up a script to check for security issues, wrap it in a -x command, and automate it to run with every build.

Automate Pull Requests with Amp

Srujana Maddula — Wed, 01 Oct 2025 12:32:17 +0000

GitHub version control tasks are something that developers mostly automate with AI today, simply because they are repetitive and common. One of the most common tasks is creating a pull request. Usually, every time you push a change to the remote repo, you need to go into the GitHub web interface and manually create a PR.

Or you can do it in commands using GitHub CLI (gh). But with Amp Code, you don’t need to run those commands or open the GitHub UI. You just tell Amp to do that for you.

Set up GitHub CLI

Amp uses GitHub CLI to seamlessly interact with your GitHub repositories, so it needs to be installed and authenticated on your system.

First, install GitHub CLI (gh) with the command below:
brew install gh

Next, run the below command and authenticate with your GitHub credentials:
gh auth login

Once the “gh” setup is complete, you can start using Amp to create and manage pull requests. Let’s see how to do that step by step.

Creating a Pull Request with Amp

Normally, you’d either:

Jump into the GitHub web interface to create a PR, or
Run a few gh commands from the terminal.

With Amp Code, you skip all that. You just tell Amp what you want. It automatically handles everything: creating a descriptive commit message, committing changes, and opening the PR.

For example, in a Streamlit project, I prompt:

“Review all the changes and create a descriptive commit message, then commit all staged and unstaged changes, then use gh to create a pull request.”

Amp then creates a TO-DO checklist, runs each step in order, and asks for approval along the way. First, it creates the commit message and commit commands and asks for approval.

We can either click “Always Run” or “Run”. “Always Run” means for similar actions, here creating a commit, Amp runs automatically from next time without your approval. “Run” option means Amp runs the commit command for this task.

Next, it asks for approval for the push command. And we can choose between “Always Run” and “Run” to push the changes.

Finally, Amp asks for approval to run the PR commands, creates the PR, and outputs the success message with the link to the PR.

When you click that link, it takes you to the created PR on GitHub.com.

We can see that Amp doesn’t just create PRs. It handles the whole flow: Reviewing changes, writing a commit message, committing staged and unstaged files, and creating the PR, all from a single prompt.

How to Add New Features with Screenshots in Amp

Srujana Maddula — Mon, 15 Sep 2025 10:38:47 +0000

Explaining code changes with long text prompts can be frustrating. Amp makes it easier: instead of typing out every detail, you can just take a screenshot of the feature you want to edit. Amp reads the screenshot, understands your instruction, and updates the codebase for you.

Example: Changing a button color in Streamlit

Let’s walk through a quick example so you can see how this works in practice.

In my Streamlit app, I have a simple “Click Me” button. I want to change its color to green.

To do that, I take a screenshot of the button and add a simple instruction (Make this button green) directly on the screenshot, as shown in the below image:

Now, I attach the above screenshot to the Amp thread and add this simple prompt: “Read the screenshot and take action.”

That’s it. Amp automatically modified my code and updated the button color to green, as shown below:

Final Thought

Using screenshots with Amp is faster, clearer, and less error-prone than writing lengthy instructions. It’s perfect for small UI tweaks, quick bug fixes, or experimenting with design changes. Sign up for Amp to explore how it simplifies your coding tasks.

How to Fix Bugs using Screenshots with Amp

Srujana Maddula — Mon, 15 Sep 2025 10:21:03 +0000

Amp is an agentic coding tool that can run in your VS-Code and as well as a command line tool in your terminal.

It's your best AI assistant in performing autonomous reasoning, comprehensive code editing, and complex task execution. You tell it what you want in plain English, and it makes the changes.

But here’s the cool part: Amp isn’t just a chatbot. You don’t always have to explain everything in text. You can drop in a screenshot with little or no context, and Amp will understand it and take the necessary action.

I’ll show you how to use Amp to fix a bug in your codebase using screenshots.

Fixing Bugs with screenshots

I have a Streamlit app in VS Code. It’s built to show different business metrics in charts. But I see a value error on the UI. Here’s how I’ll fix it with just the error screenshot.

In my Streamlit app, clicking the “Click Me” button throws the following error.

All I did was take a screenshot of this page and send it to Amp in VS Code with a short note: “Failed when I click the ‘Click Me’ button, check the screenshot for more context.”

Amp read the screenshot, understood the error, and identified relevant part of my codebase. Then it proposed a fix, showed me the changes, and after my approval applied the solution automatically.

Why Use Screenshots to Fix Bugs in Amp?

Long error messages are painful to copy and paste, and sometimes you just don’t feel like typing them into a chat window. In that case, you just simply click a photo and give it to Amp.

The tool connects the dots between what's on screenshot and the code that produced it. Because it is working directly from the actual error on screen, the solution often feels more accurate and intuitive. Therefore, this approach is more reliable as well as fast and easy. Explore the full potential of Amp here.

DEV Community: Srujana Maddula

Using Amp (AI) For Static Code Analysis

What issues does static code analysis detect?

Code duplication

SQL injection

Styling issues

Performance optimizations

Why Use Amp for static code analysis?

Different ways Amp can perform static code analysis

Amp in IDE

Amp as CLI

Amp in CI/CD

How to use Amp for static code analysis?

Conclusion

Generate Docs with Amp Code

What is Amp CLI?

Amp --execute command

Using Amp to generate project documentation

Conclusion

Automate Pull Requests with Amp

Set up GitHub CLI

Creating a Pull Request with Amp

How to Add New Features with Screenshots in Amp

Example: Changing a button color in Streamlit

Final Thought

How to Fix Bugs using Screenshots with Amp

Fixing Bugs with screenshots

Why Use Screenshots to Fix Bugs in Amp?

Amp `--execute` command