Implements adaptive logical reasoning with VRA-driven cognitive architecture for LLM agents.
npx skills add https://github.com/GrazianoGuiducci/KPhi1 --skill logic-sys
Please help me install this Agent Skill. Skill: logic-sys Source: https://github.com/GrazianoGuiducci/KPhi1/tree/main/skills/logic-sys Command: npx skills add https://github.com/GrazianoGuiducci/KPhi1 --skill logic-sys
ALAN v14.2.1 provides a robust framework for adaptive logical autopoietic reasoning in LLM agents, enabling coherent outputs across extended interactions.
Activate ALAN v14.2.1 and begin reasoning with the vE expert vectors to generate coherent responses.
High-intent search queries and answers about installing and using this skill.
To maintain coherent reasoning across long LLM interactions, an autopoietic logic network uses specialized expert vectors and meta-cognitive cycles to continuously evolve the reasoning core, ensuring consistent outputs and error checking.
Cross-domain reasoning in cognitive architecture is the ability to analyze, synthesize, and project ideas across different knowledge domains using specialized expert vectors, enabling adaptive logical autopoietic reasoning for LLM agents.
To implement an autopoietic logic network for agent reasoning, activate the ALAN v14.2.1 framework and begin reasoning with its specialized vE expert vectors to generate self-evolving, coherent responses.
A VRA-driven cognitive architecture scales from single-turn tasks to multi-turn dialogues, orchestrating expert vectors to handle cross-domain reasoning and tension-driven redesign for extended interactions.
Meta-cognition in an autopoietic reasoning system works through continuous cycles that evolve the logical network via tension-driven redesign, integrating new capabilities to extend the agent's reasoning safely.
The approach requires orchestrating multiple specialized expert vectors, meaning the system's coherence depends on the continuous autopoietic evolution and tension-driven redesign cycles to prevent reasoning degradation over long interactions.
trueraCreate and curate ground-truth evaluation datasets for TruLens.
GadaaLabsMonitor context health and compress stale reasoning during long sessions.
majesticlabs-devGenerate 30/60/90-second elevator pitches using the Villain-Hero storytelling framework.
kwoekelAnalyze prompt quality and provide prompting patterns for LLM interactions.
