Reasoningbank Intelligence
Skill ActiveImplement adaptive learning with ReasoningBank for pattern recognition, strategy optimization, and continuous improvement. Use when building self-learning agents, optimizing workflows, or implementing meta-cognitive systems.
To provide AI agents with a self-learning capability that allows them to improve their performance over time by learning from past task outcomes and optimizing their strategies.
Features
- Adaptive learning system (ReasoningBank)
- Pattern recognition from task data
- Strategy optimization and recommendation
- Continuous learning and meta-learning
- Integration with AgentDB for persistence
Use Cases
- Building self-learning agents
- Optimizing AI agent workflows
- Implementing meta-cognitive systems
- Improving strategy selection based on historical data
Non-Goals
- Performing the core tasks the agent is designed for (e.g., coding, analysis)
- Replacing the underlying LLM or agent framework
- Managing external system integrations beyond data persistence
Trust
- warning:Issues AttentionThere are 68 open issues and 373 closed issues in the last 90 days, indicating a high volume of activity but potentially slow resolution times for open issues.
Installation
npx skills add ruvnet/rufloRuns the Vercel skills CLI (skills.sh) via npx — needs Node.js locally and at least one installed skills-compatible agent (Claude Code, Cursor, Codex, …). Assumes the repo follows the agentskills.io format.
Quality Score
Trust Signals
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Observe
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Teach
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Mcp Setup
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