mouse-movement
Human-like mouse movement patterns. Use when automating browser interactions to avoid bot detection.
When & Why to Use This Skill
This Claude skill provides advanced human-like mouse movement patterns designed to enhance the reliability of web automation tasks. By implementing non-linear paths, bezier curves, and randomized timing delays, it enables AI agents to interact with web interfaces in a way that mimics authentic human behavior, effectively bypassing sophisticated bot detection mechanisms and anti-scraping security layers.
Use Cases
- Web Scraping & Data Extraction: Safely navigate and collect data from high-security websites that employ behavioral analysis to block automated scrapers.
- Automated UI/UX Testing: Simulate realistic user interactions during quality assurance processes to validate how web applications respond to natural human inputs.
- Browser Workflow Automation: Execute repetitive tasks on web-based platforms and SaaS tools without triggering security flags, CAPTCHAs, or account restrictions.
- Social Media Management: Automate engagement and navigation tasks on platforms that monitor for robotic movement patterns to maintain account integrity.
| name | mouse-movement |
|---|---|
| description | Human-like mouse movement patterns. Use when automating browser interactions to avoid bot detection. |
Mouse Movement Guidelines
Principles
- Never move in straight lines
- Add random delays between 50-200ms
- Use bezier curves for natural paths
- Vary movement speed (fast start, slow end)
Implementation Pattern
import random
import pyautogui
def human_move(x, y):
duration = random.uniform(0.3, 0.8)
pyautogui.moveTo(x, y, duration=duration, tween=pyautogui.easeOutQuad)
time.sleep(random.uniform(0.05, 0.2))
Anti-Detection Tips
- Add micro-jitters during movement
- Randomize click timing
- Simulate scroll behavior between actions