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Found 6 Skills
Quantum-resistant, self-learning version control for AI agents with ReasoningBank intelligence and multi-agent coordination
Implement ReasoningBank adaptive learning with AgentDBs 150x faster vector database. Includes trajectory tracking, verdict judgment, memory distillation, and pattern recognition. Use when building self-learning agents, optimizing decision-making, or implementing experience replay systems.
Create, restructure, and validate Claude Code skills following best practices. Handles directory structure, YAML frontmatter, progressive disclosure, credential management, self-learning with consolidation, and script organization. Use when creating new skills, restructuring existing skills, reviewing skills for quality, or asking about skill structure, patterns, or best practices.
Enables autonomous pattern recognition, storage, and retrieval at project level with self-learning capabilities for continuous improvement
A cognitive framework based on learning first principles, providing learning method diagnosis, efficiency assessment, and optimization advice. Use when: (1) Diagnosing if current learning methods align with first principles, (2) Evaluating learning plan efficiency and time investment, (3) Analyzing learning behavior problems and providing improvement suggestions, (4) Determining if learning content is worth the time investment. Core principle chain: Self-learning → Induction → Self-output → Expression restructuring → Logical understanding → Practice.
Analyze gaps between implementation plans and actual codebase implementation for the Rust self-learning memory project