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Found 10 Skills
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
Quantum-resistant, self-learning version control for AI agents with ReasoningBank intelligence and multi-agent coordination
Start a new learning episode in the self-learning memory system with proper context. Use this skill when beginning a new task that should be tracked for learning from execution patterns.
Analyze gaps between implementation plans and actual codebase implementation for the Rust self-learning memory project
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.
Use OpenClaw MemX for long-term agent memory with self-learning, relationship graphs, and automatic maintenance
Agent skill for dev-backend-api - invoke with $agent-dev-backend-api
Capture a hard-won "golden path" from the current session as a reusable Agent Skill, so future sessions start already knowing it. Use it (1) right after non-trivial debugging, after working out a multi-step operational workflow, or after rediscovering project facts you didn't know up front — e.g. how to reach the dev/prod database, where credentials and env vars live, how to deploy, run migrations, or verify a change live; and (2) whenever the user says "remember this", "save this as a skill", "make a skill for this", "don't make me re-explain this next time", or otherwise wants a workflow preserved across sessions. Proactively recognize the moment even when unprompted: if a task took several attempts before it worked, used non-obvious tooling, or is likely to recur, harvest it without asking first. Delegates to a subagent when your tool supports one, or works inline, to extract the proven procedure into a new project-local or global skill.