Prompts

Refactors a given application using 12-factor as a methodology for building software-as-a-service apps.

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.

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

Create a project diagram using PlantUML and C4 Model for your project based in your codebase

create C4 model diagram by PlantUML

Multi-prompt /dev agent prompt to create a new EKS cluster

This prompt aims to identify missing metrics/alarms related to AWS Resources in a target package. A reference package is used to limit the response to required metrics/alarms, assuming it follows best practices for the particular resource type setup.

This prompt aims to identify missing metrics/alarms related to service health in a target package. A reference package is used to limit the response to required metrics/alarms, assuming it follows best practices for service health monitoring.

This will generate ready to use python code using external libraries

Given an ADR template, provide context so Q can quickly generate the ADR

For a given selection of code, provide useful documentation to help others understand your code

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.

The prompt is useful for generating catchy titles

Update Amazon Q Knowledge of a given project

Cria a estrutura de contexto inteligente do AmazonQ para projetos de forma padronizada , conforme documentação da aws.

Frontend React Tailwind Vitests Good practices Senior Developer

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.

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.

This will generate a consistent output from /dev

Creates a pull request workflow template for Github Actions

Creates a Lambda layer zip file, given a list of Python libraries. Checks for vulnerabilities.

Create an extendable AWS architecture blueprint for a scalable file-processing pipeline, capable of handling periodic CSV file uploads for processing and notifications

Create an extendable AWS architecture blueprint using AWS CDK for an asynchronous message processing system based on the API Gateway HTTP to SQS pattern. This blueprint is designed to facilitate a scalable and decoupled system that handles incoming API requests, enqueues them in SQS, and processes them asynchronously with Lambda.

This prompt allows for creating a complete Flask-based user interface from scratch on top of this application that only exposes APIs (https://github.com/aws-containers/votingapp). I often use this for demoing Amazon Q Developer capabilities but hopefully can inspire for other type of real usage.

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

Use Amazon Q Developer to assist you in creating a step-by-step specification for a feature idea.

Adding unit tests for the code in the page

Uses the dev agent to create CDK snapshot tests following best practices and testing guidelines.

Testing constructs with fine-grained assertions focussing on covering relevant business logic, integration aspects and guardrails.