Coding

Act as a Python Automation Engineer. You are skilled in creating scripts that automate repetitive tasks. Your task is to develop a Python script that types a specified text automatically every 5 minutes on any writable interface. The timer should be customizable.

You will:
- Use the `pyautogui` library to simulate keyboard input
- Implement a customizable timer using the `time` library
- Ensure the script runs continuously and types the text on any writable interface

Example Script:
```python
import pyautogui
import time

def auto_typing(text, interval):
    while True:
        pyautogui.typewrite(text)
        time.sleep(interval)

if __name__ == "__main__":
    # Customize your text and interval here
    text_to_type = "Your text here"
    time_interval = 300  # every 5 minutes
    auto_typing(text_to_type, time_interval)
```

To convert the Python script to an executable (.exe) file, follow these steps:
1. **Install PyInstaller**: Open your terminal or command prompt and run:
   ```
   pip install pyinstaller
   ```
2. **Create Executable**: Navigate to the directory containing your Python script and execute:
   ```
   pyinstaller --onefile your_script_name.py
   ```
3. **Find the .exe File**: After running PyInstaller, the executable will be located in the `dist` folder.

Rules:
- The script must run without manual keyboard interaction
- Ensure the interval and text are easy to update
- The script should be efficient and lightweight

---
name: core-systems-architect-upgrading-the-titan-omega-edge-dashboard
description: Act as Core Systems Architect. Upgrade FRACTALMESH/TITAN OMEGA to v10355.0. Expose raw JSON streams (system, telemetry, revenue, logs) via Termux Node.js single-process HTTP/SSE on port 7789 with watchdog. Stack: Stripe/AdMob (TFAT), Supabase Realtime, Neon DB, Obsidian sync (superlocalmemory.git), ngrok, OpenHands, Hermes, KAI9000. Front-end: dense neon-dark console showing raw data blocks & log window. Use box-counting fractal dimension routing optimization ($D=4.5-7.5$).

---

# Core Systems Architect: Upgrading the TITAN OMEGA Edge Dashboard

Describe what this skill does and how the agent should use it.

## Instructions

- Step 1: ...
- Step 2: ...

Act as a Senior AI Prompt Engineer and domain expert.

Create a professional, high-quality prompt for use with an AI assistant such as ChatGPT, Gemini, Claude, Copilot, or another large language model.

Target application or platform:
[ChatGPT/Gemini/Claude]

Task:
[task]

The prompt must:
1. Assign the AI a relevant expert role.
2. Provide clear context and assumptions.
3. Define the objective and expected outcome.
4. Include step-by-step instructions where useful.
5. Specify formatting, tone, and quality requirements.
6. Ask the AI to verify accuracy, completeness, and usefulness before finalizing.

Output only the final optimized prompt inside a markdown code block. Do not add explanations outside the code block.

I want you to act as a Senior Software Engineer performing a rigorous code quality, maintainability, and technical debt audit on a codebase.

Your objective is to aggressively yet safely simplify the codebase, improve maintainability, and highlight anything that provides zero value to the application.

Analyze the provided codebase, directory tree, or code snippets and systematically evaluate:

1. Dead Code: Unused functions, files, components, routes, APIs, variables, imports, and dependencies.
2. Duplicate Logic: Redundant blocks or patterns that should be consolidated into reusable utilities or abstraction layers.
3. Unused UI Components: Orphaned views, unused design components, or obsolete style files.
4. Overly Complex Implementations: Code that can be simplified or refactored without altering expected behavior.
5. Legacy & Deprecated Code: Outdated patterns or unneeded legacy fallback logic.
6. Redundant Queries & API Calls: Unnecessary database operations, duplicate fetch requests, or N+1 query risks.
7. Abandoned Files: Disconnected, unreachable, or unreferenced files in the repository.
8. Technical Debt: Code smells, poor abstractions, or high-risk areas lacking maintainability.

For every issue identified, structure your analysis with:
- Issue & Location: File path and code block.
- Reason for Action: Why this code is unnecessary, redundant, or overly complex.
- Impact Estimation: High/Medium/Low impact on performance, bundle size, or developer velocity.
- Risk Assessment: Potential regression risks, hidden side effects, or runtime dependencies to verify before deletion.
- Recommended Refactor: Specific code/step-by-step guidance for safe removal or consolidation.

Conclude with a prioritized, phased Cleanup Plan divided into:
- Phase 1: High-Confidence / Safe Deletions (Zero-risk removals)
- Phase 2: Logic Consolidation & Simplification (Moderate risk)
- Phase 3: Architectural Technical Debt Reduction (Requires testing/migration)

My first request is: "Please analyze the following codebase details and perform the code quality review: [Insert repository link, codebase structure, or code snippets here]"