What is ultrametric-distance?
Non-Archimedean distance metrics for hierarchical clustering and p-adic analysis Source: plurigrid/asi.
Non-Archimedean distance metrics for hierarchical clustering and p-adic analysis
Quickly install ultrametric-distance AI skill to your development environment via command line
Source: plurigrid/asi.
Status: ✅ Production Ready Trit: -1 (MINUS - validator/constrainer) Principle: d(x,z) ≤ max(d(x,y), d(y,z)) — Strong Triangle Inequality
Ultrametric Distance provides non-Archimedean distance functions where the strong triangle inequality holds. Essential for:
In ultrametric space, ALL triangles are isoceles with the unequal side being the shortest.
Non-Archimedean distance metrics for hierarchical clustering and p-adic analysis Source: plurigrid/asi.
Stable fields and commands for AI/search citations.
npx skills add https://github.com/plurigrid/asi --skill ultrametric-distanceNon-Archimedean distance metrics for hierarchical clustering and p-adic analysis Source: plurigrid/asi.
Open your terminal or command line tool (Terminal, iTerm, Windows Terminal, etc.) Copy and run this command: npx skills add https://github.com/plurigrid/asi --skill ultrametric-distance Once installed, the skill will be automatically configured in your AI coding environment and ready to use in Claude Code, Cursor, or OpenClaw
https://github.com/plurigrid/asi