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Version 0.1.0 (Initial Release)

Release Date: October 2024

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🚀 New Features

  • Multi-language service layer with Python and Rust implementations
  • Progressive loading system for efficient skill content management
  • Intelligent routing with context-aware skill recommendations
  • Comprehensive skill management with registration, validation, and lifecycle operations
  • Tool calling interface for seamless skill execution
  • Event system for real-time notifications and integrations
  • Caching system with configurable TTL and persistence options

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🛠️ Implementation Details

  • Core Architecture: Modular service layer with separate components for metadata, loading, tools, and routing
  • Storage Backend: Filesystem-based storage with support for JSON and YAML skill definitions
  • Security Model: Sandboxed execution with configurable resource limits and network controls
  • Performance: In-memory caching with optional disk persistence for fast startup times
  • API Consistency: Unified interfaces across Python and Rust implementations

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📚 Documentation

  • Complete API reference for both Python and Rust SDKs
  • Getting started guides and quick start examples
  • Architecture overview and core concepts explanation
  • Installation guides for multiple platforms
  • Configuration reference with all available options

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🧪 Testing

  • 15 Python tests covering core functionality
  • 3 Rust tests for critical path validation
  • Integration tests for component interactions
  • Performance benchmarks and validation
This initial release provides a solid foundation for AI agent skill management with room for future enhancements and optimizations.

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Future Roadmap

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Planned Features (v0.2.0)

  • ZIP package support for easy skill distribution and installation
  • Hot reloading for seamless development workflows
  • Advanced security with comprehensive sandboxing
  • Web-based management interface for skill administration
  • Plugin system for extending functionality
  • Database storage backends for scalability
  • Multi-tenant support for enterprise deployments

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Enhancement Areas

  • Performance optimizations for high-throughput scenarios
  • Additional language bindings (JavaScript/TypeScript, C#, Java)
  • Cloud-native features (Kubernetes operators, Helm charts)
  • Advanced analytics and monitoring dashboards
  • Integration frameworks for popular AI agent platforms
  • Developer tooling improvements and IDE integrations

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Migration Guide

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From Development to Production

1

Review configuration

Ensure your production configuration is appropriate:
  • Disable hot reload
  • Set appropriate log levels
  • Configure proper resource limits
  • Enable audit logging
2

Validate skills

# Validate all production skills
fastskill validate ./prod-skills/

# Check for deprecated features
fastskill analyze --deprecated
3

Test deployment

# Test with production-like configuration
fastskill serve --config production.json --dry-run

# Run integration tests
fastskill test --integration

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Breaking Changes Policy

FastSkill follows semantic versioning with clear migration paths:
  • Major versions (1.x → 2.x): May include breaking API changes
  • Minor versions (x.1 → x.2): New features, backward compatible
  • Patch versions (x.y.1 → x.y.2): Bug fixes and improvements
Always review the migration guide when upgrading major versions. Test thoroughly in a staging environment before production deployment.

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Contributing to Releases

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Release Process

  1. Feature development on feature branches
  2. Testing with comprehensive test coverage
  3. Documentation updates for new features
  4. Changelog updates with clear descriptions
  5. Release candidate testing
  6. Final release with version tags

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Release Channels

  • Stable: Production-ready releases with full testing
  • Beta: Release candidates with new features for testing
  • Development: Latest changes for contributors and early adopters
Thank you to all contributors who made this release possible! Your feedback and contributions help shape FastSkill’s future direction.