Skill: bytesagain1/financial-machine-learning (version 2.0.2)

--- name: "financial-machine-learning" version: "2.0.1" description: "Reference tool for devtools — covers intro, quickstart, patterns and more. Quick lookup for Financial Machine Learning concepts, best practices, and implemen..." author: "BytesAgain" homepage: "https://bytesagain.com" source: "https://github.com/bytesagain/ai-skills" tags: [financial,machine,learning, reference] category: "devtools" --- # Financial Machine Learning Reference tool for devtools — covers intro, quickstart, patterns and more. Quick lookup for Financial Machine Learning concepts, best practices, and implemen... No API keys or credentials required. ## Commands | Command | Description | |---------|-------------| | `intro` | intro reference | | `quickstart` | quickstart reference | | `patterns` | patterns reference | | `debugging` | debugging reference | | `performance` | performance reference | | `security` | security reference | | `migration` | migration reference | | `cheatsheet` | cheatsheet reference | ## Output Format All commands output plain-text reference documentation via heredoc. No external API calls, no credentials needed, no network access. --- *Powered by BytesAgain | bytesagain.com | [REDACTED_SECRET]*

path: scripts/script.sh
content: #!/usr/bin/env bash
# financial-machine-learning — Financial Machine Learning reference tool. Use when working with financial machine learning in devtools contexts.
# Powered by BytesAgain | bytesagain.com | [REDACTED_SECRET]
set -euo pipefail

VERSION="2.0.0"

show_help() {
    cat << 'HELPEOF'
financial-machine-learning v$VERSION — Financial Machine Learning Reference Tool

Usage: financial-machine-learning <command>

Commands:
  intro           Overview and core concepts
  quickstart      Getting started guide
  patterns        Common patterns and best practices
  debugging       Debugging and troubleshooting
  performance     Performance optimization tips
  security        Security considerations
  migration       Migration and upgrade guide
  cheatsheet      Quick reference cheat sheet
  help              Show this help
  version           Show version

Powered by BytesAgain | bytesagain.com
HELPEOF
}

cmd_intro() {
    cat << 'EOF'
# Financial Machine Learning — Overview

## What is Financial Machine Learning?
Financial Machine Learning (financial-machine-learning) is a specialized tool/concept in the devtools domain.
It provides essential capabilities for professionals working with financial machine learning.

## Key Concepts
- Core financial machine learning principles and fundamentals
- How financial machine learning fits into the broader devtools ecosystem  
- Essential terminology every practitioner should know

## Why Financial Machine Learning Matters
Understanding financial machine learning is critical for:
- Improving efficiency in devtools workflows
- Reducing errors and downtime
- Meeting industry standards and compliance requirements
- Enabling better decision-making with accurate data

## Getting Started
1. Understand the basic financial machine learning concepts
2. Learn the standard tools and interfaces
3. Practice with common scenarios
4. Review safety and compliance requirements
EOF
}

cmd_quickstart() {
    cat << 'EOF'
# Financial Machine Learning — Quick Start Guide

## Prerequisites
- Basic understanding of devtools concepts
- Required tools and access credentials
- System meeting minimum requirements

## Installation
1. Download or clone the financial machine learning package
2. Install dependencies
3. Configure initial settings
4. Verify installation

## First Steps
1. Run the hello-world example
2. Review the default configuration
3. Try a simple real-world task
4. Explore available commands and options

## Next Steps
- Read the full documentation
- Join the community forum
- Try advanced features
- Set up automated workflows
EOF
}

cmd_patterns() {
    cat << 'EOF'
# Financial Machine Learning — Common Patterns & Best Practices

## Design Patterns
1. **Standard Pattern**: The most common approach for financial machine learning
2. **Scalable Pattern**: For high-volume or distributed scenarios
3. **Resilient Pattern**: For fault-tolerant implementations

## Best Practices
- Follow the principle of least privilege
- Use version control for all configurations
- Implement comprehensive logging
- Test changes in staging before production
- Document all custom configurations

## Anti-Patterns to Avoid
- Hardcoding credentials or configuration
- Skipping validation and error handling
- Ignoring monitoring and alerting
- Making changes without documentation
- Over-engineering simple solutions
EOF
}

cmd_debugging() {
    cat << 'EOF'
# Financial Machine Learning — Debugging Guide

## Common Errors
1. **Connection refused**: Check service status and network
2. **Permission denied**: Verify credentials and access rights
3. **Timeout**: Check network, increase limits, optimize queries
4. **Invalid input**: Validate data format and encoding

## Debugging Tools
- Built-in logging and diagnostics
- Network analysis tools (tcpdump, wireshark)
- System monitoring (top, htop, iostat)
- Application-specific debug modes

## Debug Workflow
1. Reproduce the issue consistently
2. Check logs for error messages
3. Isolate the failing component
4. Test with minimal configuration
5. Apply fix and verify
EOF
}

cmd_performance() {
    cat << 'EOF'
# Financial Machine Learning — Performance Optimization

## Key Metrics
- Response time / latency
- Throughput / operations per second
- Resource utilization (CPU, memory, I/O)
- Error rate and retry frequency

## Optimization Strategies
1. **Caching**: Reduce redundant operations
2. **Batching**: Group small operations
3. **Indexing**: Speed up data lookups
4. **Compression**: Reduce data transfer size
5. **Parallel Processing**: Utilize multiple cores

## Monitoring
- Set up baseline performance metrics
- Configure alerts for anomalies
- Track trends over time
- Regular capacity planning reviews
EOF
}

cmd_security() {
    cat << 'EOF'
# Financial Machine Learning — Security Considerations

## Authentication & Authorization
- Use strong, unique credentials
- Implement role-based access control
- Enable multi-factor authentication where possible
- Regularly review and rotate credentials

## Data Protection
- Encrypt data at rest and in transit
- Implement proper backup procedures
- Follow data retention policies
- Sanitize inputs to prevent injection

## Network Security
- Use firewalls and network segmentation
- Monitor for suspicious activity
- Keep all software patched and updated
- Disable unnecessary services and ports
EOF
}

cmd_migration() {
    cat << 'EOF'
# Financial Machine Learning — Migration & Upgrade Guide

## Pre-Migration Checklist
- [ ] Current system fully documented
- [ ] Complete backup taken and verified
- [ ] Target environment prepared
- [ ] Rollback plan documented
- [ ] Stakeholders notified

## Migration Steps
1. Prepare target environment
2. Export data from source
3. Transform data if needed
4. Import to target
5. Verify data integrity
6. Update configurations
7. Test all functionality
8. Switch traffic / go live

## Post-Migration
- Monitor for errors and performance
- Verify all integrations working
- Update documentation
- Decommission old system after confirmation
EOF
}

cmd_cheatsheet() {
    cat << 'EOF'
# Financial Machine Learning — Quick Reference

## Essential Commands
| Command | Description |
|---------|-------------|
| help | Show available commands |
| version | Display version info |
| intro | Overview and fundamentals |
| troubleshooting | Common problems and fixes |

## Common Workflows
1. **Setup**: install → configure → verify → test
2. **Daily**: check → monitor → report → review
3. **Issue**: diagnose → isolate → fix → verify → document

## Key Shortcuts
- Use tab completion for commands
- Check logs first when troubleshooting
- Always backup before making changes
- Document everything you change
EOF
}

CMD="${1:-help}"
shift 2>/dev/null || true

case "$CMD" in
    intro) cmd_intro "$@" ;;
    quickstart) cmd_quickstart "$@" ;;
    patterns) cmd_patterns "$@" ;;
    debugging) cmd_debugging "$@" ;;
    performance) cmd_performance "$@" ;;
    security) cmd_security "$@" ;;
    migration) cmd_migration "$@" ;;
    cheatsheet) cmd_cheatsheet "$@" ;;
    help|--help|-h) show_help ;;
    version|--version|-v) echo "financial-machine-learning v$VERSION — Powered by BytesAgain" ;;
    *) echo "Unknown: $CMD"; echo "Run: financial-machine-learning help"; exit 1 ;;
esac


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)