linux-production-shell-scripts▌
sickn33/antigravity-awesome-skills · updated Apr 8, 2026
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Provide production-ready shell script templates for common Linux system administration tasks including backups, monitoring, user management, log analysis, and automation. These scripts serve as building blocks for security operations and penetration testing environments.
Linux Production Shell Scripts
Purpose
Provide production-ready shell script templates for common Linux system administration tasks including backups, monitoring, user management, log analysis, and automation. These scripts serve as building blocks for security operations and penetration testing environments.
Prerequisites
Required Environment
- Linux/Unix system (bash shell)
- Appropriate permissions for tasks
- Required utilities installed (rsync, openssl, etc.)
Required Knowledge
- Basic bash scripting
- Linux file system structure
- System administration concepts
Outputs and Deliverables
- Backup Solutions - Automated file and database backups
- Monitoring Scripts - Resource usage tracking
- Automation Tools - Scheduled task execution
- Security Scripts - Password management, encryption
Core Workflow
Phase 1: File Backup Scripts
Basic Directory Backup
#!/bin/bash
backup_dir="/path/to/backup"
source_dir="/path/to/source"
# Create a timestamped backup of the source directory
tar -czf "$backup_dir/backup_$(date +%Y%m%d_%H%M%S).tar.gz" "$source_dir"
echo "Backup completed: backup_$(date +%Y%m%d_%H%M%S).tar.gz"
Remote Server Backup
#!/bin/bash
source_dir="/path/to/source"
remote_server="user@remoteserver:/path/to/backup"
# Backup files/directories to a remote server using rsync
rsync -avz --progress "$source_dir" "$remote_server"
echo "Files backed up to remote server."
Backup Rotation Script
#!/bin/bash
backup_dir="/path/to/backups"
max_backups=5
# Rotate backups by deleting the oldest if more than max_backups
while [ $(ls -1 "$backup_dir" | wc -l) -gt "$max_backups" ]; do
oldest_backup=$(ls -1t "$backup_dir" | tail -n 1)
rm -r "$backup_dir/$oldest_backup"
echo "Removed old backup: $oldest_backup"
done
echo "Backup rotation completed."
Database Backup Script
#!/bin/bash
database_name="your_database"
db_user="username"
db_pass="password"
output_file="database_backup_$(date +%Y%m%d).sql"
# Perform database backup using mysqldump
mysqldump -u "$db_user" -p"$db_pass" "$database_name" > "$output_file"
gzip "$output_file"
echo "Database backup created: $output_file.gz"
Phase 2: System Monitoring Scripts
CPU Usage Monitor
#!/bin/bash
threshold=90
# Monitor CPU usage and trigger alert if threshold exceeded
cpu_usage=$(top -bn1 | grep "Cpu(s)" | awk '{print $2}' | cut -d. -f1)
if [ "$cpu_usage" -gt "$threshold" ]; then
echo "ALERT: High CPU usage detected: $cpu_usage%"
# Add notification logic (email, slack, etc.)
# mail -s "CPU Alert" [email protected] <<< "CPU usage: $cpu_usage%"
fi
Disk Space Monitor
#!/bin/bash
threshold=90
partition="/dev/sda1"
# Monitor disk usage and trigger alert if threshold exceeded
disk_usage=$(df -h | grep "$partition" | awk '{print $5}' | cut -d% -f1)
if [ "$disk_usage" -gt "$threshold" ]; then
echo "ALERT: High disk usage detected: $disk_usage%"
# Add alert/notification logic here
fi
CPU Usage Logger
#!/bin/bash
output_file="cpu_usage_log.txt"
# Log current CPU usage to a file with timestamp
timestamp=$(date '+%Y-%m-%d %H:%M:%S')
cpu_usage=$(top -bn1 | grep 'Cpu(s)' | awk '{print $2}' | cut -d. -f1)
echo "$timestamp - CPU Usage: $cpu_usage%" >> "$output_file"
echo "CPU usage logged."
System Health Check
#!/bin/bash
output_file="system_health_check.txt"
# Perform system health check and save results to a file
{
echo "System Health Check - $(date)"
echo "================================"
echo ""
echo "Uptime:"
uptime
echo ""
echo "Load Average:"
cat /proc/loadavg
echo ""
echo "Memory Usage:"
free -h
echo ""
echo "Disk Usage:"
df -h
echo ""
echo "Top Processes:"
ps aux --sort=-%cpu | head -10
} > "$output_file"
echo "System health check saved to $output_file"
Phase 3: User Management Scripts
User Account Creation
#!/bin/bash
username="newuser"
# Check if user exists; if not, create new user
if id "$username" &>/dev/null; then
echo "User $username already exists."
else
useradd -m -s /bin/bash "$username"
echo "User $username created."
# Set password interactively
passwd "$username"
fi
Password Expiry Checker
#!/bin/bash
output_file="password_expiry_report.txt"
# Check password expiry for users with bash shell
echo "Password Expiry Report - $(date)" > "$output_file"
echo "=================================" >> "$output_file"
IFS=$'\n'
for user in $(grep "/bin/bash" /etc/passwd | cut -d: -f1); do
password_expires=$(chage -l "$user" 2>/dev/null | grep "Password expires" | awk -F: '{print $2}')
echo "User: $user - Password Expires: $password_expires" >> "$output_fileHow to use linux-production-shell-scripts on Cursor
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Prerequisites
Before installing skills in Cursor, ensure your development environment meets these requirements:
- ›Cursor installed and configured on your development machine
- ›Node.js version 16.0+ with npm package manager (verify with
node --version) - ›Active project directory or workspace where you want to add linux-production-shell-scripts
Execute installation command
Execute the skills CLI command in your project's root directory to begin installation:
The skills CLI fetches linux-production-shell-scripts from GitHub repository sickn33/antigravity-awesome-skills and configures it for Cursor.
Select Cursor when prompted
The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:
Verify installation
Confirm successful installation by checking the skill directory location:
Reload or restart Cursor to activate linux-production-shell-scripts. Access the skill through slash commands (e.g., /linux-production-shell-scripts) or your agent's skill management interface.
Security & Verification Notice
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.
List & Monetize Your Skill
Submit your Claude Code skill and start earning
Use Cases▌
User Story & Requirements Generation
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Competitive Analysis
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Roadmap Prioritization
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
Make data-driven prioritization decisions faster
Stakeholder Communication
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Implementation Guide▌
Prerequisites
- ›Claude Desktop or compatible AI client
- ›Access to product documentation and roadmap tools (Jira, Notion, etc.)
- ›Understanding of product management frameworks (RICE, Jobs-to-be-Done, etc.)
- ›Stakeholder contact information and communication channels
Time Estimate
30-60 minutes to see productivity improvements
Installation Steps
- 1.Install product management skill
- 2.Start with user story generation for known feature
- 3.Progress to competitive analysis: research 2-3 competitors
- 4.Use for roadmap prioritization: apply RICE/ICE scoring
- 5.Draft stakeholder communications and refine based on feedback
- 6.Build template library for recurring PM tasks
- 7.Share effective prompts with product team
Common Pitfalls
- ⚠Not validating competitive research—verify facts before sharing
- ⚠Accepting user stories without involving engineering team
- ⚠Over-relying on frameworks without qualitative judgment
- ⚠Not customizing outputs to company culture and communication style
- ⚠Skipping stakeholder validation of generated requirements
Best Practices▌
✓ Do
- +Validate research and competitive analysis with real data
- +Collaborate with engineering when generating technical requirements
- +Customize frameworks and templates to your company context
- +Use skill for first drafts, refine with stakeholder input
- +Document successful prompt patterns for PM tasks
- +Combine AI efficiency with human judgment and intuition
✗ Don't
- −Don't publish competitive analysis without fact-checking
- −Don't finalize user stories without engineering review
- −Don't make prioritization decisions solely on AI scoring
- −Don't skip customer validation of generated requirements
- −Don't ignore company-specific context and culture
💡 Pro Tips
- ★Provide context: company goals, constraints, customer feedback
- ★Ask for alternatives: 'Show 3 ways to prioritize this roadmap'
- ★Request stakeholder-specific formatting: 'Executive summary vs. engineering spec'
- ★Use skill for 70% generation + 30% customization to company needs
When to Use This▌
✓ Use When
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid When
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
Learning Path▌
- 1Basic: user stories, feature specs, status updates
- 2Intermediate: competitive analysis, prioritization frameworks, PRDs
- 3Advanced: product strategy, go-to-market planning, OKR setting
- 4Expert: product vision, market positioning, business model innovation
Discussion
Product Hunt–style comments (not star reviews)- No comments yet — start the thread.
Ratings
4.4★★★★★26 reviews- ★★★★★Fatima Khanna· Dec 20, 2024
I recommend linux-production-shell-scripts for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
- ★★★★★Evelyn Gill· Dec 16, 2024
linux-production-shell-scripts has been reliable in day-to-day use. Documentation quality is above average for community skills.
- ★★★★★Yusuf Ndlovu· Nov 11, 2024
Keeps context tight: linux-production-shell-scripts is the kind of skill you can hand to a new teammate without a long onboarding doc.
- ★★★★★Yusuf Okafor· Oct 2, 2024
linux-production-shell-scripts is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.
- ★★★★★Yash Thakker· Sep 17, 2024
We added linux-production-shell-scripts from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Michael Lopez· Sep 5, 2024
We added linux-production-shell-scripts from the explainx registry; install was straightforward and the SKILL.md answered most questions upfront.
- ★★★★★Zara Chen· Aug 24, 2024
linux-production-shell-scripts fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Dhruvi Jain· Aug 8, 2024
linux-production-shell-scripts fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
- ★★★★★Oshnikdeep· Jul 27, 2024
Registry listing for linux-production-shell-scripts matched our evaluation — installs cleanly and behaves as described in the markdown.
- ★★★★★Evelyn White· Jul 15, 2024
Registry listing for linux-production-shell-scripts matched our evaluation — installs cleanly and behaves as described in the markdown.
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