Six core capabilities for intelligent skill management
Creative skill discovery with hierarchical skill tree for semantic navigation
DAG-based workflow with automatic dependency management and parallel execution
Built-in GUI for controllable, auditable workflows with human oversight
Curated skills based on GitHub stars and downloads, ensuring reliability
Trace logs and metadata for debugging and monitoring skill execution
Flexible registry for custom skills with easy integration and management
Three key components for intelligent skill management
Comparing semantic retrieval vs. our LLM + Skill Tree approach
▲ Left: Pure semantic retrieval prioritizes textual similarity, often missing skills that look unrelated in embedding space but are crucial for solving the task—leading to narrow, myopic skill usage.
▲ Right: Our LLM + Skill Tree navigates the capability hierarchy to surface non-obvious but functionally relevant skills, enabling broader, more creative, and more effective skill composition.
Click to see detailed workflow and results
Auto-locate frontend bugs and generate visual diagnosis reports
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Research Notion/Confluence design patterns, generate concept designs
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Academic paper → Multi-platform social media promotional materials
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Green screen video → Viral short video with subtitles & voiceover
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