A prompt designed to guide a deep technical analysis of a code repository to accelerate developer onboarding. It instructs an AI to analyze the entire codebase and generate a structured Markdown document covering architecture, technology stack, key components, execution and data flows, integrations, testing, security, and build/deployment, serving as a technical reference guide.
**Context:**
I am a developer who has just joined the project and I am using you, an AI coding assistant, to gain a deep understanding of the existing codebase. My goal is to become productive as quickly as possible and to make informed technical decisions based on a solid understanding of the current system.
**Primary Objective:**
Analyze the source code provided in this project/workspace and generate a **detailed, clear, and well-structured Markdown document** that explains the system’s architecture, features, main flows, key components, and technology stack.
This document should serve as a **technical onboarding guide**.
Whenever possible, improve navigability by providing **direct links to relevant files, classes, and functions**, as well as code examples that help clarify the concepts.
---
## **Detailed Instructions — Please address the following points:**
### 1. **README / Instruction Files Summary**
- Look for files such as `README.md`, `LEIAME.md`, `CONTRIBUTING.md`, or similar documentation.
- Provide an objective yet detailed summary of the most relevant sections for a new developer, including:
- Project overview
- How to set up and run the system locally
- Adopted standards and conventions
- Contribution guidelines (if available)
---
### 2. **Detailed Technology Stack**
- Identify and list the complete technology stack used in the project:
- Programming language(s), including versions when detectable (e.g., from `package.json`, `pom.xml`, `.tool-versions`, `requirements.txt`, `build.gradle`, etc.).
- Main frameworks (backend, frontend, etc. — e.g., Spring Boot, .NET, React, Angular, Vue, Django, Rails).
- Database(s):
- Type (SQL / NoSQL)
- Name (PostgreSQL, MongoDB, etc.)
- Core architecture style (e.g., Monolith, Microservices, Serverless, MVC, MVVM, Clean Architecture).
- Cloud platform (if identifiable via SDKs or configuration — AWS, Azure, GCP).
- Build tools and package managers (Maven, Gradle, npm, yarn, pip).
- Any other relevant technologies (caching, message brokers, containerization — Docker, Kubernetes).
- **Reference and link the configuration files that demonstrate each item.**
---
### 3. **System Overview and Purpose**
- Clearly describe what the system does and who it is for.
- What problems does it solve?
- List the core functionalities.
- If possible, relate the system to the business domains involved.
- Provide a high-level description of the main features.
---
### 4. **Project Structure and Reading Recommendations**
- **Entry Point:**
Where should I start exploring the code? Identify the main entry points (e.g., `main.go`, `index.js`, `Program.cs`, `app.py`, `Application.java`).
**Provide direct links to these files.**
- **General Organization:**
Explain the overall folder and file structure. Highlight important conventions.
**Use real folder and file name examples.**
- **Configuration:**
Are there main configuration files? (e.g., `config.yaml`, `.env`, `appsettings.json`)
Which configurations are critical?
**Provide links.**
- **Reading Recommendation:**
Suggest an order or a set of key files/modules that should be read first to quickly grasp the project’s core concepts.
---
### 5. **Key Components**
- Identify and describe the most important or central modules, classes, functions, or services.
- Explain the responsibilities of each component.
- Describe their responsibilities and interdependencies.
- For each component:
- Include a representative code snippet
- Provide a link to where it is implemented
- **Provide direct links and code examples whenever possible.**
---
### 6. **Execution and Data Flows**
- Describe the most common or critical workflows or business processes (e.g., order processing, user authentication).
- Explain how data flows through the system:
- Where data is persisted
- How it is read, modified, and propagated
- **Whenever possible, illustrate with examples and link to relevant functions or classes.**
#### 6.1 **Database Schema Overview (if applicable)**
- For data-intensive applications:
- Identify the main entities/tables/collections
- Describe their primary relationships
- Base this on ORM models, migrations, or schema files if available
---
### 7. **Dependencies and Integrations**
- **Dependencies:**
List the main external libraries, frameworks, and SDKs used.
Briefly explain the role of each one.
**Provide links to where they are configured or most commonly used.**
- **Integrations:**
Identify and explain integrations with external services, additional databases, third-party APIs, message brokers, etc.
How does communication occur?
**Point to the modules/classes responsible and include links.**
#### 7.1 **API Documentation (if applicable)**
- If the project exposes APIs:
- Is there evidence of API documentation tools or standards (e.g., Swagger/OpenAPI, Javadoc, endpoint-specific docstrings)?
- Where can this documentation be found or how can it be generated?
---
### 8. **Diagrams**
- Generate high-level diagrams to visualize the system architecture and behavior:
- Component diagram (highlighting main modules and their interactions)
- Data flow diagram (showing how information moves through the system)
- Class diagram (showing key classes and relationships, if applicable)
- Simplified deployment diagram (where components run, if detectable)
- Simplified infrastructure/deployment diagram (if infrastructure details are apparent)
- **Create these diagrams using Mermaid syntax inside the Markdown file.**
- Diagrams should be **high-level**; extensive detailing is not required.
---
### 9. **Testing**
- Are there automated tests?
- Unit tests
- Integration tests
- End-to-end (E2E) tests
- Where are they located in the project?
- Which testing framework(s) are used?
- How are tests typically executed?
- How can tests be run locally?
- Is there any CI/CD strategy involving tests?
---
### 10. **Error Handling and Logging**
- How does the application generally handle errors?
- Is there a standard pattern (e.g., global middleware, custom exceptions)?
- Which logging library is used?
- Is there a standard logging format?
- Is there visible integration with monitoring tools (e.g., Datadog, Sentry)?
---
### 11. **Security Considerations**
- Are there evident security mechanisms in the code?
- Authentication
- Authorization (middleware/filters)
- Input validation
- Are specific security libraries prominently used (e.g., Spring Security, Passport.js, JWT libraries)?
- Are there notable security practices?
- Secrets management
- Protection against common attacks
---
### 12. **Other Relevant Observations (Including Build/Deploy)**
- Are there files related to **build or deployment**?
- `Dockerfile`
- `docker-compose.yml`
- Build/deploy scripts
- CI/CD configuration files (e.g., `.github/workflows/`, `.gitlab-ci.yml`)
- What do these files indicate about how the application is built and deployed?
- Is there anything else crucial or particularly helpful for a new developer?
- Known technical debt mentioned in comments
- Unusual design patterns
- Important coding conventions
- Performance notes
---
## **Final Output Format**
- Generate the complete response as a **well-formatted Markdown (`.md`) document**.
- Use **clear and direct language**.
- Organize content with **titles and subtitles** according to the numbered sections above.
- **Include relevant code snippets** (short and representative).
- **Include clickable links** to files, functions, classes, and definitions whenever a specific code element is mentioned.
- Structure the document using the numbered sections above for readability.
**Whenever possible:**
- Include **clickable links** to files, functions, and classes.
- Show **short, representative code snippets**.
- Use **bullet points or tables** for lists.
---
### **IMPORTANT**
The analysis must consider **ALL files in the project**.
Read and understand **all necessary files** required to fully execute this task and achieve a complete understanding of the system.
---
### **Action**
Please analyze the source code currently available in my environment/workspace and generate the Markdown document as requested.
The output file name must follow this format:
`<yyyy-mm-dd-project-name-app-dev-discovery_cursor.md>`