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Agent skill

Memory Management

by ruvnet in ruvnet/ruflo

AgentDB memory system with HNSW vector search. An agent skill from ruvnet/ruflo.

MITAuto-check passedDatabases

Install Memory Management

skills CLI
$ npx skills add ruvnet/ruflo --skill memory-management -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install ruvnet/ruflo memory-management --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/ruvnet/ruflo.git skills-src && mkdir -p .claude/skills && cp -r skills-src/v3/@claude-flow/codex/.agents/skills/memory-management .claude/skills/memory-management && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
memory-management
GitHub stars
74k
Token cost
~231 tokens
SKILL.md length
72 words
Files
1
Skills in repo
264
Repo updated
First seen
Licence
MIT

At a glance

AgentDB memory system with HNSW vector search. An agent skill from ruvnet/ruflo.

  • Works in 4 steps: Check memory for existing patterns… → Use hierarchical topology for coordination → Store successful patterns after completion → …
  • : need to store patterns
  • SKILL.md covers Purpose, When to Trigger, When to Skip and Commands, plus 1 more section
  • Calls npx

What it does

Memory Management is an agent skill from ruvnet/ruflo. AgentDB memory system with HNSW vector search. Use when: need to store patterns, search for solutions, semantic lookup. Skip when: no learning needed, ephemeral tasks.

Its SKILL.md is about 230 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Databases, covering Vector databases. The repository describes itself as: 🌊 The original agent harness. Deploy intelligent multi-player swarms, coordinate autonomous workflows, and build conversational AI systems. Features adaptive memory…. The licence is MIT.

When your agent uses it

  • : need to store patterns
  • Search for solutions
  • Semantic lookup

Example prompts

  • “/memory-management”

Requirements

  • Node.js

Workflow steps

4 steps, taken from the first numbered list in SKILL.md.

  1. Check memory for existing patterns before starting
  2. Use hierarchical topology for coordination
  3. Store successful patterns after completion
  4. Document any new learnings

What it can do on your machine

Read from SKILL.md and the folder at commit de590e1. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • npx

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use npx, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Memory Management loads about 231 tokens when it runs. Until then it costs about 46 tokens; SKILL.md has 72 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~46
When it runs · the whole SKILL.md, loaded when a task matches
~231

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from ruvnet/ruflo at commit de590e1, republished under its MIT licence (© ruvnet). 72 words, ~231 tokens.

Download SKILL.mdSave it as .claude/skills/memory-management/SKILL.md (or your agent's skills folder).
name
memory-management
description
AgentDB memory system with HNSW vector search. Use when: need to store patterns, search for solutions, semantic lookup. Skip when: no learning needed, ephemeral tasks.

Memory Management Skill

Purpose

AgentDB memory system with HNSW vector search.

When to Trigger

  • need to store patterns
  • search for solutions
  • semantic lookup

When to Skip

  • no learning needed
  • ephemeral tasks

Commands

Store Data

Store a pattern in memory

bash
npx @claude-flow/cli memory store --key "key" --value "value" --namespace patterns
Search Data

Semantic search in memory

bash
npx @claude-flow/cli memory search --query "search terms" --limit 10

Best Practices

  1. Check memory for existing patterns before starting
  2. Use hierarchical topology for coordination
  3. Store successful patterns after completion
  4. Document any new learnings

© ruvnet, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in v3/@claude-flow/codex/.agents/skills/memory-management of ruvnet/ruflo.

Open the folder on GitHubat commit de590e1

Compare with similar skills

Memory Management next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Memory Management compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Memory Management this skillruvnet/ruflo74k—~231Automated safety check: PassMIT
Codebase Explorationgiancarloerra/SocratiCode3.3k1 repos~1.5kAutomated safety check: PassAGPL-3.0
FAISS Similarity SearchOrchestra-Research/AI-Research-SKILLs13k7 repos~1.3kAutomated safety check: PassMIT
Weaviateweaviate/agent-skills105—~1.8kAutomated safety check: PassBSD-3-Clause
Pinecone Vector DatabaseOrchestra-Research/AI-Research-SKILLs13k6 repos~2kAutomated safety check: PassMIT
Qdrant Vector SearchOrchestra-Research/AI-Research-SKILLs13k5 repos~3.4kAutomated safety check: PassMIT

Similar skills

  • Codebase Exploration

    giancarloerra/SocratiCode

    Explore and understand codebases using SocratiCode semantic search, dependency graphs, and context artifacts.

    3.3k GitHub starsUsed in 1 repo~1.5k tokens
    DatabasesAuto-check passed

  • FAISS Similarity Search

    Orchestra-Research/AI-Research-SKILLs

    Sets up FAISS for fast nearest-neighbor search over large collections of dense vectors, choosing between Flat, IVF, HNSW and product quantization indexes.

    13k GitHub starsUsed in 7 repos~1.3k tokens
    DatabasesAuto-check passed

  • Weaviate

    weaviate/agent-skills

    Official

    Search, query, and manage Weaviate vector database collections.

    105 GitHub stars~1.8k tokensUpdated yesterday
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  • Pinecone Vector Database

    Orchestra-Research/AI-Research-SKILLs

    Shows how to use Pinecone, a managed vector database, for production RAG, semantic search and recommendations: indexes, upserts, queries, filters and namespaces.

    13k GitHub starsUsed in 6 repos~2k tokens
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  • Qdrant Vector Search

    Orchestra-Research/AI-Research-SKILLs

    Explains how to run Qdrant, a Rust vector database, for RAG and semantic search, covering collections, points, distance metrics and filtered or batched queries.

    13k GitHub starsUsed in 5 repos~3.4k tokens
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More from ruvnet/ruflo

All 264 skills in this repo

  • AgentDB Pattern Memory

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    Stores, searches, and retrieves successful patterns with HNSW-indexed semantic search so agents can reuse past solutions instead of relearning them.

    74k GitHub starsUsed in 2 repos~830 tokens
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  • Security Audit Scanner

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    Runs claude-flow CLI security scans for input validation, path traversal, SQL injection, XSS, hardcoded secrets and known CVEs, and writes an audit report.

    74k GitHub starsUsed in 2 repos~823 tokens
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  • SPARC Development Methodology

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    Applies the SPARC method (specification, pseudocode, architecture, refinement, completion) with 17 specialized modes and multi-agent orchestration, from research to deployment.

    74k GitHub starsUsed in 2 repos~829 tokens
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  • Swarm Orchestration

    ruvnet/ruflo

    Coordinates a hierarchical swarm of specialized agents through the claude-flow CLI for work that spans several files or modules at once.

    74k GitHub starsUsed in 2 repos~779 tokens
    Auto-check passed

  • Ruflo Multi-Agent Orchestration

    ruvnet/ruflo

    Sets up and drives Ruflo, an npm-installed orchestration layer for multi-agent swarms, persistent memory, routing, hooks and its MCP tool catalog.

    74k GitHub starsUsed in 1 repo~975 tokens
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  • Agent Coordination

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    Reference for spawning, listing, monitoring and stopping agents with claude-flow commands, with agent type families, routing codes and coordination tips.

    74k GitHub starsUsed in 2 repos~519 tokens
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Categories

Questions about Memory Management

What does Memory Management do?

AgentDB memory system with HNSW vector search. An agent skill from ruvnet/ruflo. Memory Management is an agent skill from ruvnet/ruflo. AgentDB memory system with HNSW vector search.

When should I use Memory Management?

Memory Management fits situations like: : need to store patterns; search for solutions; semantic lookup.

How do I install Memory Management in Claude Code?

Run `npx skills add ruvnet/ruflo --skill memory-management -a claude-code`. Or copy the skill folder (v3/@claude-flow/codex/.agents/skills/memory-management in ruvnet/ruflo) into .claude/skills/memory-management in your project. Claude Code loads it when a task matches its description.

How do I install Memory Management in Codex?

Run `npx skills add ruvnet/ruflo --skill memory-management -a codex`. Or copy the skill folder (v3/@claude-flow/codex/.agents/skills/memory-management in ruvnet/ruflo) into .agents/skills/memory-management in your project. Codex loads it when a task matches its description.

Can I use Memory Management in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add ruvnet/ruflo --skill memory-management -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/memory-management, .gemini/skills/memory-management, .github/skills/memory-management and .opencode/skills/memory-management in your project.

What does Memory Management need to run?

Going by SKILL.md and its folder, Memory Management needs the command-line tools its instructions call (npx). Our summary lists: Node.js.

Does Memory Management access the network?

SKILL.md contains no URLs. Its commands use npx, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Memory Management safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Memory Management use?

Memory Management is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Memory Management use?

About 231 tokens (SKILL.md is roughly 924 characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Memory Management?

Skills that share tags, products or a category with Memory Management: Codebase Exploration (giancarloerra/SocratiCode, 3.3k stars), FAISS Similarity Search (Orchestra-Research/AI-Research-SKILLs, 13k stars), Weaviate (weaviate/agent-skills, 105 stars) and Pinecone Vector Database (Orchestra-Research/AI-Research-SKILLs, 13k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Memory Management?

ruvnet (a GitHub user) maintains it in ruvnet/ruflo, which has 74,012 GitHub stars. The repository holds 264 skills in this directory. The repository was last updated on October 7, 2026.

Source: ruvnet/ruflo on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.