X Auto Like Bot automates the repetitive process of liking posts on social media platforms like Instagram. By using Android automation, this bot mimics user interactions and automates the task of liking posts, saving time and effort for businesses or individuals managing multiple accounts. The bot is designed to enhance engagement with minimal manual effort.
X Auto Like Bot is an automation tool designed to interact with social media posts automatically. It performs the repetitive task of liking posts based on specific criteria or predefined schedules, which saves time and increases engagement for social media marketers, influencers, or anyone looking to automate their interactions. The tool works by simulating user actions on Android devices using standard automation frameworks.
- Time-saving automation: Automates the process of liking posts to reduce manual effort.
- Customizable behavior: Supports scheduling and customizable engagement actions.
- Scalable: Can be run on multiple devices simultaneously for large-scale automation.
- Efficient: Can be configured to operate at different speeds, balancing efficiency and resource use.
- Robust error handling: Includes retries, logging, and alerts for high reliability.
| Feature | Description |
|---|---|
| Task Scheduler | Schedule auto likes at set times or intervals. |
| User Interaction | Simulates user gestures like scrolling, liking, and commenting. |
| Device Control | Allows control over multiple Android devices simultaneously. |
| Proxy Support | Integrates proxy management to simulate different user locations. |
| Smart Filters | Filters posts based on hashtags, keywords, or user interactions. |
| Randomization | Randomizes actions to mimic human-like behavior. |
| Error Handling | Automatic retries, backoff strategies, and logging for failures. |
| Performance Metrics | Provides detailed logs on actions performed and success rates. |
| Multi-Account Support | Manage multiple accounts simultaneously with individual settings. |
| Real-Time Monitoring | Monitor and control active tasks in real time via a dashboard. |
Input or Trigger — The user sets criteria such as hashtags, time intervals, and target accounts for auto liking. Core Logic — The bot uses automation tools to simulate user interactions like liking posts based on input criteria. Output or Action — Likes are applied to qualifying posts automatically at the set times. Other Functionalities — The bot logs each action, handles retries for failures, and sends notifications for important updates. Safety Controls — Implements rate limiting, action throttling, and human-like randomization to avoid detection.
List core technologies used: Language: Python Frameworks: Appium, UI Automator Tools: ADB, Task Scheduler Infrastructure: Android Emulator, Proxy servers
automation-bot/
├── src/
│ ├── main.py
│ ├── automation/
│ │ ├── tasks.py
│ │ ├── scheduler.py
│ │ └── utils/
│ │ ├── logger.py
│ │ ├── proxy_manager.py
│ │ └── config_loader.py
├── config/
│ ├── settings.yaml
│ ├── credentials.env
├── logs/
│ └── activity.log
├── output/
│ ├── results.json
│ └── report.csv
├── requirements.txt
└── README.md
- Social media marketers use it to automate engagement across multiple platforms, so they can focus on content creation and strategy.
- Influencers use it to manage their engagement across different accounts, so they can grow their audience faster without spending hours on manual interaction.
- Businesses use it to automate routine tasks like liking posts for brand visibility, so they can improve their social media presence with minimal effort.
Q: Is X Auto Like Bot safe to use? A: Yes, the bot includes safety controls like action randomization and rate limiting to avoid detection by social media platforms.
Q: How many accounts can I manage at once? A: You can manage multiple accounts at once, and the bot is scalable, allowing for simultaneous operation across many devices.
Q: Can I schedule likes? A: Yes, the bot allows you to schedule likes at specific times or intervals to optimize engagement.
Execution Speed: Capable of performing 100–200 actions per minute per device under normal conditions. Success Rate: 93–95% success rate with retries on long-running jobs. Scalability: Can handle 300–1,000 Android devices using distributed queues and horizontal workers. Resource Efficiency: Targets around 100MB of RAM and 1 CPU core per worker on typical devices. Error Handling: Features auto-retries, backoff strategies, and structured logging to recover from errors automatically.
