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Skills/AI & Agent Building
ruvnet avatar

Memory Management

ruvnet/ruflo

This is AgentDB's vector memory system with HNSW search that claims 150x to 12,500x faster pattern retrieval than whatever baseline they're comparing against.

installs
1.2K
GitHub stars
79.3K
last updated
Aug 21, 2026
View on GitHubSave

Install

$ npx -y skills add ruvnet/ruflo --skill memory-management --agent claude-code

Installs into .claude/skills of the current project.

Sponsors

CodeRabbitSponsoredTry For FreeLid closed, agents workingTry itAppSignalSponsoredStart Free TrialKeep API keys from agentsGet SnugBlock apps on your iPhoneGet WaxDevtools for design engineersTry it livebelt - the only tool your agent needsSponsoredone prompt installOpen StepsSponsoredDownload for free

What it does

You get persistent storage for successful patterns, semantic search across past work, and the ability to share knowledge between agents. The workflow is straightforward: check memory before starting tasks, store what worked, consolidate periodically. It's overkill for one-off scripts but makes sense if you're running agents that should learn from previous sessions or need to avoid solving the same problem twice. The CLI covers the basics with store, search, and export commands, plus you can initialize HNSW indexing separately if you want the speed boost.

Files

Select a file.

Details

Repository
github.com/ruvnet/ruflo
Category
AI & Agent Building
First seen
Jun 3, 2026

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