#CLI

Update Amazon Q Knowledge of a given project

Learn from sketchy things you did in your CLI in the past and their risks

Let Q do a code review of your staged files before committing and pushing your changes.

Commit you changes to git with a meaningful commit message following conventional commit specification.

This prompt creates a shell script to copy data from a target DynamoDB table to a source table.

This prompt assists you to calculate costs for your workload using up-to-date pricing information from the AWS service websites.

Generates realistic user personas based on your existing documentation or customer descriptions.

Writes a git commit message using information about your current git repository and staged changes.

Automate the creation of Github pull requests.

Let Amazon Q create an implementation plan as a sequence of prompts that can be executed to implement a feature or task.

Transforms Amazon Q into a critical thinking partner that challenges your ideas instead of simply agreeing. The AI questions your assumptions, offers skeptical viewpoints, checks your reasoning for flaws, suggests alternative perspectives, and prioritizes accuracy over agreement. Perfect for refining arguments, avoiding confirmation bias, and developing more robust thinking.

Analyzed and summarized an Eclipe MAT report with clear, actionable insights.

Generate comprehensive JUnit 5 tests for the selected Java code/function/class using best practices and design patterns.

Transforms Amazon Q into a speaking coach that analyzes presentation videos, providing detailed feedback on delivery, body language, and content structure. Creates multiple analysis files including comprehensive feedback, timestamp-specific notes, talk structure outline, and a personalized scorecard based on your experience level. Organizes outputs for easy reference and future analyses.

The project intelligence documentation system transforms Amazon Q Developer from a stateless assistant into a persistent development partner by providing comprehensive context about your application.

Prompt to send Q CLI Chat to do research on recent libraries for you.

Analyzes a React-based application and generates documentation visualizing the component hierarchy, component relationships, and key component metadata.

Security review.

Use the CLI to install all your development tools from a .zshrc file. Without it, the manual setup would have taken hours. The CLI completes the task in minutes.

Amazon Q Developer operates more quickly, more accurately, and consistently when properly configured with information it can load quickly. This prompt instructs Q to learn from your project and create context-efficient files that give Q just what it needs, with references to load-on-demand details based on the interaction.

Looking at your code and find new areas that needs to be tested

Let Amazon Q prepare your Well-Architected Review, based on an analysis of a provided Cloudformation template

This document explains the standardized naming convention for Amazon Q learning files across different projects and directories.

Project rules to steer Amazon Q Developer for all things related to implementing authentication with AWS Amplify Gen2

Project rules to tune Amazon Q Developer in all things related to data modeling and modeling relationships with AWS Amplify Gen2

Outlines best practices for developing AWS CDK constructs. Following these guidelines will ensure that constructs are reusable, maintainable, and follow AWS best practices.

Outlines recommended design patterns for AWS CDK development. Design patterns are reusable solutions to common problems in software development. Following these patterns will ensure consistency, maintainability, and scalability across the codebase. The patterns described here are particularly relevant for AWS CDK development.

This document outlines the recommended project structure for AWS CDK applications. A well-organized project structure is critical for maintainability, scalability, and developer onboarding. Following these guidelines will ensure consistency across the codebase and make navigation easier as the project grows.

Outlines security and compliance best practices for AWS CDK applications. Security is a critical aspect of infrastructure as code, and following these guidelines will help ensure that your CDK applications are secure, compliant, and follow AWS best practices.

Outlines best practices for testing AWS CDK applications. Testing is a critical aspect of CDK development to ensure that infrastructure is deployed correctly and behaves as expected. Following these guidelines will help create reliable, maintainable, and well-tested infrastructure code.

TypeScript best practices for AWS CDK development. Following these guidelines will ensure type safety, code consistency, and maintainability across the codebase. TypeScript's static typing capabilities help catch errors early in the development process and provide better tooling support.

Helps Q Developer to optimize the creation of end-to-end tests for playwright. Main source for these rules are the best practices listed at the official playwright documentation.

Empowers Amazon Q Developer to maintain Kiro specifications to apply spec-driven developmen the Kiro way.

Run a AI-driven exploratory test on mobile device and generate test report. based on that, you could either generate a full airtest script project or adjust existing project.

Next.js rules used to build promptz.dev

The project intelligence documentation system transforms Amazon Q Developer from a stateless assistant into a persistent development partner by providing comprehensive context about your application across various sessions. Once the rule was added to your repository, you can ask Q Developer to initialize the project intelligence with "Initialize Project Intelligence". If already in place, you can force an update by asking Q "Update Project Intelligence".

Reverse-Engineered Xcode's Coding Intelligence prompt to be used as Amazon Q Developer Projet Rule

Operational troubleshooting and root cause analysis of incidents in your AWS Account

Keeps your Github backlog up-to-date with feature requests and bug fixes.

Enable effective collaboration between product teams, engineering teams, and AI agents. The goal is to make all engineers within a team leverage spec-driven development following the standards of Kiro in any IDE.

Maintains the documentation system called Project Intelligence as a living documentation for both human engineers and AI assistants. The goal is to help engineers improve their productivity by providing detailed and up-to-date documentation. Make sure to also use the project-intelligence project rules available via promptz.dev.

Create frontend experiences following TDD based on Next.js, tailwind, and shadcn that are blazing fast, accessible to all users, and delightful to interact with. The agent is designed to use the github CLI and project-intelligence concept of promptz.dev. Adjust the system prompt to your needs if your tooling or documentation concept differs.