Orchestrates complex skill ecosystems using graph-based neighbor analysis and triadic routing.
The Skill Connectivity Hub is an advanced orchestration layer designed to manage and optimize interactions between numerous specialized Claude Code skills. By analyzing the connectivity and 'out-degree' of skills using Babashka and Narya, it identifies high-impact 'hub skills' to streamline task routing and ensure efficient information flow. This skill maintains architectural coherence through GF(3) triadic conservation and provides robust tools for counterfactual diffing, allowing developers to track and verify how individual skill evolutions impact the broader topological ecosystem.
Key Features
01Graph-based skill orchestration via neighbor-aware interleaving
02Native Emacs and libghosty VT integration for formal verification
03Babashka-powered connectivity analysis for identifying hub skills
042 GitHub stars
05Counterfactual diffing for tracking skill evolution with Narya proofs
06GF(3) triadic routing to ensure compositional coherence
Use Cases
01Verifying structural invariants and connectivity after skill updates
02Optimizing routing paths for complex, multi-step AI agent workflows
03Managing large-scale modular AI skill repositories with high interconnectivity
