What's New in v2.0

Intelligent System Design Generation

The flagship feature of v2.0 is the Architecture Reasoning Engine - an AI-powered system that analyzes project requirements and generates comprehensive system designs.

+----------------------------------------------------------------------------------------+
| TARGET: MoneyGuard - RECOMMENDED BACKEND ARCHITECTURE                                  |
+----------------------------------------------------------------------------------------+
|                                                                                        |
| DOMAIN: Fintech (High Sensitivity)                                                     |
| PATTERN: Event-Driven Architecture (EDA) + Micro-segmentation                          |
|                                                                                        |
| CORE STACK:                                                                            |
|   - Language: Go (Fiber) / Rust (Actix)                                                |
|   - Messaging: Apache Kafka / RabbitMQ                                                 |
|   - Auth: OAuth2 + OIDC (Keycloak)                                                     |
|                                                                                        |
| DATABASE STRATEGY:                                                                     |
|   - Primary: PostgreSQL (ACID compliant)                                               |
|   - Caching: Redis (Cluster mode)                                                      |
|   - Immutable: Amazon QLDB (Ledger for transactions)                                   |
|                                                                                        |
| SECURITY PROTOCOLS:                                                                    |
|   - Encryption: AES-256 (At rest) + mTLS (In transit)                                  |
|   - Resilience: Circuit Breakers + Throttling                                          |
|                                                                                        |
| ANTI-PATTERNS TO AVOID:                                                                |
|   - [!] No Firebase for core financial ledger                                          |
|   - [!] No client-side balance calculations                                            |
|                                                                                        |
| PRE-DELIVERY CHECKLIST:                                                                |
|   [ ] Idempotency keys implemented on all write APIs                                   |
|   [ ] Distributed Tracing (OpenTelemetry) configured                                   |
|   [ ] Secrets managed via HashiCorp Vault                                              |
|                                                                                        |
+----------------------------------------------------------------------------------------+

Features

• 100+ Industry Rules: Architecture reasoning for Fintech, HealthTech, SaaS, Web3, AI platforms, E-commerce, and more.
• 18 Data Categories: Comprehensive CSV knowledge base covering architecture, databases, security, testing, cloud patterns, and observability.
• Architecture Persistence: Decisions are automatically saved to BACKEND_MASTER.md for reference.
• Security Protocols: Hardened checklists based on OWASP Top 10, HIPAA, PCI-DSS, and GDPR.
• Performance Optimization: Intelligent recommendations for indexing, caching, and low-latency throughput.
• Testing Strategies: Unit, integration, E2E, performance, and security testing patterns.
• Cloud Patterns: AWS, GCP, Azure, and multi-cloud architecture recommendations.
• Multi-Agent Support: Native integration for 11+ AI coding assistants.

Installation

Using CLI (Recommended)

Navigate to your project directory and run:

cd /path/to/your/project
npx backend-promax-skill init

One-line Installer (No Node.js Required)

Windows (PowerShell):

cd C:\path\to\your\project
iwr -useb https://raw.githubusercontent.com/dsoftodin22999/backend-promax-skill/main/install.ps1 | iex

Mac / Linux:

cd /path/to/your/project
curl -fsSL https://raw.githubusercontent.com/dsoftodin22999/backend-promax-skill/main/install.sh | sh

Local Installation (From Cloned Repo)

.\install_to_project.ps1 -TargetProject "C:\path\to\your\project"

📖 For detailed integration instructions, see INTEGRATION.md

Quick Start Guide

Step 1: Install to Your Project

cd my-project
npx backend-promax-skill init

Step 2: Open Your AI Coding Assistant

Open your project in Cursor, Windsurf, Claude Code, or any supported AI agent.

Step 3: Generate Architecture

Type in the chat:

/backend-pro-max "E-commerce" "MarketplaceApp"

Step 4: Review the Output

Check the generated BACKEND_MASTER.md file for your architecture recommendations.

Step 5: Continue Development

Ask follow-up questions:

"Based on BACKEND_MASTER.md, create the initial folder structure."

"Implement the database schema following the architecture report."

Available Commands

| Command | Description | Example | | :--- | :--- | :--- | | /backend-pro-max [industry] [project] | Generate full architecture report | /backend-pro-max "Fintech" "PaymentApp" | | /backend-db [data_type] | Database selection recommendation | /backend-db "real-time chat" | | /backend-secure | Security audit of current code | /backend-secure | | /backend-test [project_type] | Testing strategy recommendations | /backend-test "microservices" | | /backend-cloud [service] | Cloud service comparison | /backend-cloud "compute" | | /backend-observability | Observability tool recommendations | /backend-observability |

AI Agent Integration

| Agent | Integration Method | | :--- | :--- | | Antigravity | Slash Commands: /backend-pro-max, /backend-db, /backend-secure | | Cursor / Windsurf | Slash Command: /backend-pro-max [industry] [project] | | Claude Code | Automatic via .claude/skills/ | | GitHub Copilot | Select from prompts menu or type @backend-promax | | Gemini CLI | Native support via .gemini/skills/ | | Kiro | Integrated via .kiro/steering/ | | Roo Code | Native support via .roo/rules/ | | Codex CLI | Integrated via .codex/skills/ | | Qoder | Integrated via .qoder/skills/ | | Trae IDE | Integrated via .trae/skills/ |

Example Prompts

Generate Architecture:

/backend-pro-max "Fintech" "CryptoExchange"

Database Selection:

Based on the database-decision-matrix, recommend the optimal storage for a real-time chat application.

Security Audit:

Audit my current API code against the security checklist.

Testing Strategy:

What testing strategy should I use for this microservices architecture?

Cloud Recommendations:

Compare AWS Lambda vs Cloud Run for my serverless API.

Knowledge Base

The skill includes 18 comprehensive data files:

| Category | Files | | :--- | :--- | | Architecture | backend-reasoning.csv, architecture-patterns.csv, tech-stacks.csv | | Database | database-decision-matrix.csv, caching-strategies.csv | | Security | security-deep-dive.csv, anti-patterns.csv | | Performance | performance-optimization-guide.csv, reliability-strategies.csv | | API Design | api-design-guidelines.csv, api-versioning-guide.csv, error-handling-patterns.csv | | Testing | testing-strategies.csv | | Cloud | cloud-patterns.csv | | Observability | observability-stack.csv | | DevOps | devops-deployment.csv | | Edge Cases | edge-case-reasoning.csv, pre-delivery-checklist.csv |

Running the Reasoning Engine Manually

You can run the reasoning engine directly using Python:

# Generate architecture report
python .shared/backend-promax/search_logic.py "Fintech" --system-design --project "MyApp" --persist

# Search for database recommendations
python .shared/backend-promax/search_logic.py "cache" --domain database-decision-matrix

# Search for security guidelines
python .shared/backend-promax/search_logic.py "authentication" --domain security-deep-dive

# Search for testing strategies
python .shared/backend-promax/search_logic.py "api" --domain testing-strategies

System Flow

graph LR
    A[Requirement] --> B{Reasoning Engine}
    B --> C[(18 Data Categories)]
    C --> D[Architecture Report]
    D --> E[BACKEND_MASTER.md]
    E --> F[Code Implementation]

Documentation

• INTEGRATION.md - Detailed integration guide
• CLAUDE.md - Quick reference for Claude Code users

License

MIT License - See LICENSE for details.