Agent skill

Agenticx Memory Architect

Guide for setting up and using the AgenticX memory system including Mem0 integration, long-term memory, context management, and memory-enhanced agents.

Apache-2.0Auto-check passedAgent Workflows

Install Agenticx Memory Architect

skills CLI

$ npx skills add DemonDamon/AgenticX --skill agenticx-memory-architect -a claude-code

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

GitHub CLI

$ gh skill install DemonDamon/AgenticX agenticx-memory-architect --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/DemonDamon/AgenticX.git skills-src && mkdir -p .claude/skills && cp -r skills-src/agenticx/skills/agenticx-memory-architect .claude/skills/agenticx-memory-architect && 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/

Paste into Claude Code

Install the "agenticx-memory-architect" agent skill from https://github.com/DemonDamon/AgenticX/tree/main/agenticx/skills/agenticx-memory-architect into .claude/skills/agenticx-memory-architect/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "agenticx-memory-architect", then confirm the skill loads.

Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

$skill-installer

$skill-installer install https://github.com/DemonDamon/AgenticX/tree/main/agenticx/skills/agenticx-memory-architect

Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.

skills CLI

$ npx skills add DemonDamon/AgenticX --skill agenticx-memory-architect -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install DemonDamon/AgenticX agenticx-memory-architect --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/DemonDamon/AgenticX.git skills-src && mkdir -p .agents/skills && cp -r skills-src/agenticx/skills/agenticx-memory-architect .agents/skills/agenticx-memory-architect && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "agenticx-memory-architect" agent skill from https://github.com/DemonDamon/AgenticX/tree/main/agenticx/skills/agenticx-memory-architect into .agents/skills/agenticx-memory-architect/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "agenticx-memory-architect", then confirm the skill loads.

Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add DemonDamon/AgenticX --skill agenticx-memory-architect -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install DemonDamon/AgenticX agenticx-memory-architect --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/DemonDamon/AgenticX.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/agenticx/skills/agenticx-memory-architect .cursor/skills/agenticx-memory-architect && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "agenticx-memory-architect" agent skill from https://github.com/DemonDamon/AgenticX/tree/main/agenticx/skills/agenticx-memory-architect into .cursor/skills/agenticx-memory-architect/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "agenticx-memory-architect", then confirm the skill loads.

Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

gemini skills install

$ gemini skills install https://github.com/DemonDamon/AgenticX.git --path agenticx/skills/agenticx-memory-architect

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add DemonDamon/AgenticX --skill agenticx-memory-architect -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install DemonDamon/AgenticX agenticx-memory-architect --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/DemonDamon/AgenticX.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/agenticx/skills/agenticx-memory-architect .gemini/skills/agenticx-memory-architect && rm -rf skills-src

Use ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.

Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/

Paste into Gemini CLI

Install the "agenticx-memory-architect" agent skill from https://github.com/DemonDamon/AgenticX/tree/main/agenticx/skills/agenticx-memory-architect into .gemini/skills/agenticx-memory-architect/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "agenticx-memory-architect", then confirm the skill loads.

Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

GitHub CLI

$ gh skill install DemonDamon/AgenticX agenticx-memory-architect

Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).

skills CLI

$ npx skills add DemonDamon/AgenticX --skill agenticx-memory-architect -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/DemonDamon/AgenticX.git skills-src && mkdir -p .github/skills && cp -r skills-src/agenticx/skills/agenticx-memory-architect .github/skills/agenticx-memory-architect && rm -rf skills-src

Use ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.

GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/

Paste into GitHub Copilot

Install the "agenticx-memory-architect" agent skill from https://github.com/DemonDamon/AgenticX/tree/main/agenticx/skills/agenticx-memory-architect into .github/skills/agenticx-memory-architect/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "agenticx-memory-architect", then confirm the skill loads.

GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add DemonDamon/AgenticX --skill agenticx-memory-architect -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install DemonDamon/AgenticX agenticx-memory-architect --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/DemonDamon/AgenticX.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/agenticx/skills/agenticx-memory-architect .opencode/skills/agenticx-memory-architect && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "agenticx-memory-architect" agent skill from https://github.com/DemonDamon/AgenticX/tree/main/agenticx/skills/agenticx-memory-architect into .opencode/skills/agenticx-memory-architect/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "agenticx-memory-architect", then confirm the skill loads.

OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

Facts

Skill name: agenticx-memory-architect
GitHub stars: 315
Token cost: ~1.1k tokens
SKILL.md length: 184 words
Files: 1
Skills in repo: 17
Repo updated: Oct 9, 2026
First seen: Oct 7, 2026
Licence: Apache-2.0

At a glance

Guide for setting up and using the AgenticX memory system including Mem0 integration, long-term memory, context management, and memory-enhanced agents.

Works in 7 steps: Scope memories — always associate with… → Dedup — check for similar memories… → TTL — set expiration for time-sensitive… → …
The user wants to add memory to agents
SKILL.md covers Overview, Installation, Memory System Components and Basic Memory Usage, plus 6 more sections
Calls python and pip

What it does

Agenticx Memory Architect is an agent skill from DemonDamon/AgenticX. Guide for setting up and using the AgenticX memory system including Mem0 integration, long-term memory, context management, and memory-enhanced agents. Use when the user wants to add memory to agents, persist conversation history, build memory-aware workflows, or integrate with Mem0 for long-term recall.

Its SKILL.md is about 1.1k 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 Agent Workflows, covering Agent memory, Context engineering and Vector databases. It works with Mem0, Milvus and Qdrant. The repository describes itself as: AgenticX is a unified, production-ready multi-agent platform — Python SDK + CLI (agx) + Studio server + Machi desktop app. Features Meta-Agent orchestration, 15+ LLM providers… The licence is Apache-2.0.

When your agent uses it

The user wants to add memory to agents
Persist conversation history
Build memory-aware workflows
Integrate with Mem0 for long-term recall

Example prompts

“/agenticx-memory-architect”

Requirements

Python 3

Workflow steps

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

Scope memories — always associate with user_id and/or agent_id
Dedup — check for similar memories before adding
TTL — set expiration for time-sensitive information
Privacy — never store PII without consent; use data isolation
Vector store selection — ChromaDB for dev, Qdrant/Milvus for production
Memory extraction — automate fact extraction from conversations
Test retrieval — verify that stored memories are actually retrievable

What it can do on your machine

Read from SKILL.md and the folder at commit ce32aff. 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:
- python
- pip
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md. Its commands use pip, 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

Agenticx Memory Architect loads about 1.1k tokens when it runs. Until then it costs about 83 tokens; SKILL.md has 184 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~83
When it runs · the whole SKILL.md, loaded when a task matches: ~1.1k

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 DemonDamon/AgenticX at commit ce32aff, republished under its Apache-2.0 licence (© DemonDamon). 184 words, ~1,122 tokens.

Download SKILL.mdSave it as .claude/skills/agenticx-memory-architect/SKILL.md (or your agent's skills folder).

name: agenticx-memory-architect
description: Guide for setting up and using the AgenticX memory system including Mem0 integration, long-term memory, context management, and memory-enhanced agents. Use when the user wants to add memory to agents, persist conversation history, build memory-aware workflows, or integrate with Mem0 for long-term recall.
metadata.author: AgenticX
metadata.version: 0.6.5

AgenticX Memory Architect

Guide for building agents with persistent memory capabilities.

Overview

AgenticX integrates with Mem0 for long-term memory, providing agents with the ability to remember past interactions, learn from experience, and maintain context across sessions.

Installation

bash

pip install "agenticx[memory]"
# Includes: mem0, chromadb, qdrant-client, redis, milvus

Memory System Components

Component	Purpose
`MemoryManager`	Core memory management interface
`Mem0Integration`	Bridge to Mem0's memory engine
`ContextMemory`	Short-term, session-scoped memory
`LongTermMemory`	Persistent, cross-session memory

Basic Memory Usage

Initialize Memory

python

from agenticx.memory import MemoryManager

memory = MemoryManager(
    provider="mem0",
    config={
        "llm": {"provider": "openai", "config": {"model": "gpt-4"}},
        "vector_store": {"provider": "chroma"}
    }
)

Store and Retrieve

python

# Add a memory
memory.add(
    content="User prefers concise reports with bullet points",
    user_id="user-123",
    agent_id="analyst"
)

# Search memories
results = memory.search(
    query="What format does the user prefer?",
    user_id="user-123"
)
for r in results:
    print(f"[{r.score:.2f}] {r.content}")

# Get all memories for a user
all_memories = memory.get_all(user_id="user-123")

Memory-Enhanced Agents

Attach Memory to an Agent

python

from agenticx import Agent, AgentExecutor
from agenticx.memory import MemoryManager
from agenticx.llms import OpenAIProvider

memory = MemoryManager(provider="mem0")
agent = Agent(
    id="assistant",
    name="Personal Assistant",
    role="Assistant with memory",
    goal="Help users while remembering their preferences",
    organization_id="default"
)

executor = AgentExecutor(
    agent=agent,
    llm=OpenAIProvider(model="gpt-4"),
    memory=memory
)

# First interaction — learns preference
result = executor.run(task_1)

# Later interaction — recalls preference
result = executor.run(task_2)  # agent remembers context from task_1

Memory Extraction

AgenticX can automatically extract memorable facts from conversations:

python

from agenticx.core.memory_extraction import MemoryExtractor

extractor = MemoryExtractor(llm=llm)
facts = extractor.extract(conversation_history)
# facts: ["User is a data scientist", "Prefers Python over R", ...]

for fact in facts:
    memory.add(content=fact, user_id="user-123")

Vector Store Backends

Backend	Config key	Best for
ChromaDB	`"chroma"`	Local development, small scale
Qdrant	`"qdrant"`	Production, high performance
Redis	`"redis"`	Fast access, ephemeral
Milvus	`"milvus"`	Large scale, distributed

python

# Qdrant example
memory = MemoryManager(
    provider="mem0",
    config={
        "vector_store": {
            "provider": "qdrant",
            "config": {"host": "localhost", "port": 6333}
        }
    }
)

Healthcare Example

python

# Medical knowledge memory
memory.add(
    content="Patient has Type 2 diabetes, diagnosed 2023",
    user_id="patient-456",
    metadata={"category": "medical_history"}
)

# Query with context
results = memory.search(
    query="What chronic conditions does the patient have?",
    user_id="patient-456"
)

CLI Memory Operations

bash

# Run the memory example
python examples/memory_example.py

# Healthcare scenario
python examples/mem0_healthcare_example.py

Best Practices

Scope memories — always associate with user_id and/or agent_id
Dedup — check for similar memories before adding
TTL — set expiration for time-sensitive information
Privacy — never store PII without consent; use data isolation
Vector store selection — ChromaDB for dev, Qdrant/Milvus for production
Memory extraction — automate fact extraction from conversations
Test retrieval — verify that stored memories are actually retrievable

Files

Just SKILL.md in agenticx/skills/agenticx-memory-architect of DemonDamon/AgenticX.

Open the folder on GitHubat commit ce32aff

Compare with similar skills

Agenticx Memory Architect 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.

Agenticx Memory Architect compared with similar skills
Skill	Stars	Used in	Tokens	Auto-check	Licence	Repo updated
Agenticx Memory Architect this skillDemonDamon/AgenticX	315	—	~1.1k	Automated safety check: Pass	Apache-2.0	today
Agent Memory Systemsaiskillstore/marketplace	430	3 repos	~7.8k	Automated safety check: Pass	None	today
Cognee Community Packagestopoteretes/cognee	32k	—	~1.2k	Automated safety check: Pass	Apache-2.0	today
Mem0 Bridgemomori777/Artemis	378	—	~453	Automated safety check: Pass	Custom licence	8 days ago
Cortex Mem MCPsopaco/cortex-mem	313	—	~2.8k	Automated safety check: Pass	MIT	2 mo ago
Agent Memory Systemsomer-metin/skills-for-antigravity	162	—	~731	Automated safety check: Pass	Apache-2.0	8 mo ago

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Works with

Questions about Agenticx Memory Architect

What does Agenticx Memory Architect do?

Guide for setting up and using the AgenticX memory system including Mem0 integration, long-term memory, context management, and memory-enhanced agents. Agenticx Memory Architect is an agent skill from DemonDamon/AgenticX. Guide for setting up and using the AgenticX memory system including Mem0 integration, long-term memory, context management, and memory-enhanced agents.

When should I use Agenticx Memory Architect?

Agenticx Memory Architect fits situations like: the user wants to add memory to agents; persist conversation history; build memory-aware workflows; integrate with Mem0 for long-term recall.

How do I install Agenticx Memory Architect in Claude Code?

Run `npx skills add DemonDamon/AgenticX --skill agenticx-memory-architect -a claude-code`. Or copy the skill folder (agenticx/skills/agenticx-memory-architect in DemonDamon/AgenticX) into .claude/skills/agenticx-memory-architect in your project. Claude Code loads it when a task matches its description.

How do I install Agenticx Memory Architect in Codex?

Run `npx skills add DemonDamon/AgenticX --skill agenticx-memory-architect -a codex`. Or copy the skill folder (agenticx/skills/agenticx-memory-architect in DemonDamon/AgenticX) into .agents/skills/agenticx-memory-architect in your project. Codex loads it when a task matches its description.

Can I use Agenticx Memory Architect 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 DemonDamon/AgenticX --skill agenticx-memory-architect -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/agenticx-memory-architect, .gemini/skills/agenticx-memory-architect, .github/skills/agenticx-memory-architect and .opencode/skills/agenticx-memory-architect in your project.

What does Agenticx Memory Architect need to run?

Going by SKILL.md and its folder, Agenticx Memory Architect needs the command-line tools its instructions call (python and pip). Our summary lists: Python 3.

Does Agenticx Memory Architect access the network?

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

Is Agenticx Memory Architect 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 Agenticx Memory Architect use?

Agenticx Memory Architect is published under the Apache-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Agenticx Memory Architect use?

About 1.1k tokens (SKILL.md is roughly 4.5k 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 Agenticx Memory Architect?

Skills that share tags, products or a category with Agenticx Memory Architect: Agent Memory Systems (aiskillstore/marketplace, 430 stars), Cognee Community Packages (topoteretes/cognee, 32k stars), Mem0 Bridge (momori777/Artemis, 378 stars) and Cortex Mem MCP (sopaco/cortex-mem, 313 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Agenticx Memory Architect?

DemonDamon (a GitHub user) maintains it in DemonDamon/AgenticX, which has 315 GitHub stars. The repository holds 17 skills in this directory. The repository was last updated on October 9, 2026.

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

Install Agenticx Memory Architect

Facts

At a glance

What it does

When your agent uses it

Example prompts

Requirements

Workflow steps

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

AgenticX Memory Architect

Overview

Installation

Memory System Components

Basic Memory Usage

Initialize Memory

Store and Retrieve

Memory-Enhanced Agents

Attach Memory to an Agent

Memory Extraction

Vector Store Backends

Healthcare Example

CLI Memory Operations

Best Practices

Files

Compare with similar skills

Similar skills

More from DemonDamon/AgenticX

Related

Questions about Agenticx Memory Architect