Reasoningbank With Agentdb
CheckedReasoningbank With Agentdb provides structured logical inferences and contextual data retrieval, boosting informed decision-making & problem-solving.
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reasoningbank-with-agentdb. ruvnet/ruflo has no skill named "reasoningbank-with-agentdb" any more. It was renamed, moved or deleted upstream.We check each listing against its upstream repository with the rules the skills CLI uses, last on 2026-10-22. We don't show a command we know will fail.
What we know about this skill
Publisher
ruvnet
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Install target
Live repository
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Automated safety checks
This skill passed all 6 checks. We read its files at one commit and looked for the things that make a skill dangerous to run — not for whether it works.
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SKILL.md parses and declares a name and a description.
SKILL.md exists, its frontmatter parses, and it declares a name and a description.
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Makes no network calls.
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Scanned ruvnet/claude-flow at 49da6ecc44.
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About this skill
What it does
Reasoningbank With Agentdb enables AI agents to learn from experiences and improve decision-making over time by utilizing adaptive learning patterns stored within an AgentDB backend. It provides a high-performance solution (up to 12,500x faster than previous implementations) for retrieving these patterns and performing batch operations. This skill ensures backward compatibility while offering significant performance improvements in memory access (<1ms).
When to use it
- When you need an AI agent to learn from past interactions and adjust its behavior accordingly.
- For applications requiring rapid retrieval of logical inferences or contextual data for informed decision-making.
- To enhance problem-solving capabilities by allowing agents to distill memories and analyze outcomes.
Key capabilities
- Adaptive learning patterns using AgentDB.
- High-performance backend (150x faster pattern retrieval, 500x faster batch operations).
- Fast memory access (<1ms).
- 100% backward compatibility with previous Reasoningbank implementations.
- Learning and reasoning agent plugins.
Example prompts
- "Agent, based on past experiences, how should I approach this database query optimization problem?"
- "Can you retrieve the most successful strategies for handling similar situations as this one?"
- “What patterns have been observed in previous attempts to solve problems like this?”
Tips & gotchas
- Requires Node.js 18+ and AgentDB v1.0.7+.
- Familiarity with reinforcement learning concepts is optional but can be helpful for understanding the skill's functionality.
- To initialize, use
npx agentdb@latest init ./.agentdb$reasoningbank.db --dimension 1536.