
agentic-stack-portable-agent-memory
Portable .agent/ folder with memory, skills, and protocols that works across Claude Code, Cursor, Windsurf, and other AI coding harnesses
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Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/reason-machines/ai-agent-skills --skill agentic-stack-portable-agent-memory- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads agentic-stack-portable-agent-memory automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
agentic-stack-portable-agent-memory
Skill by ara.so — AI Agent Skills collection.
What It Does
agentic-stack creates a portable .agent/ folder that maintains memory, skills, and protocols across different AI coding harnesses (Claude Code, Cursor, Windsurf, OpenCode, OpenClaw, Copilot CLI, Gemini, Hermes, Pi, Codex, Antigravity). When you switch tools, your agent keeps its knowledge, preferences, and accumulated context.
It includes:
- Memory layers: personal, semantic, episodic, working memory
- Skills system: reusable capabilities with manifest tracking
- Data layer: monitor harness activity, token/cost estimates, KPI summaries
- Data flywheel: turn approved runs into training artifacts
- Brain integration: optional git-backed long-term memory
- Harness manager: TUI for managing multiple adapters simultaneously
Installation
macOS / Linux
# Tap and install (both lines required)
brew tap codejunkie99/agentic-stack https://github.com/codejunkie99/agentic-stack
brew install agentic-stack
# Install into your project
cd your-project
agentic-stack claude-code
Windows (PowerShell)
git clone https://github.com/codejunkie99/agentic-stack.git
cd agentic-stack
.\install.ps1 claude-code C:\path\to\your-project
Clone Method
git clone https://github.com/codejunkie99/agentic-stack.git
cd agentic-stack
./install.sh claude-code
Upgrade Existing Installation
brew update && brew upgrade agentic-stack
cd your-project
agentic-stack upgrade --dry-run
agentic-stack upgrade --yes
Available Adapters
claude-code- Anthropic Claude Codecursor- Cursor IDEwindsurf- Windsurfopencode- OpenCodeopenclaw- OpenClawcopilot-cli- GitHub Copilot CLIgemini- Google Gemini CLIhermes- Hermespi- Pi Coding Agentcodex- Codexstandalone-python- DIY Python loopantigravity- Antigravity
Key Commands
Project Management
# Interactive dashboard
agentic-stack dashboard
# Web-based mission control (beta)
agentic-stack mission-control
# Check adapter status
agentic-stack status
# Audit installation health
agentic-stack doctor
# Interactive adapter manager
agentic-stack manage
# Add additional adapter
agentic-stack add cursor
# Remove adapter
agentic-stack remove cursor
Upgrade & Sync
# Preview infrastructure updates
agentic-stack upgrade --dry-run
# Apply updates (preserves memory and custom skills)
agentic-stack upgrade --yes
# Rebuild skill manifest
agentic-stack sync-manifest
Brain Integration (Optional)
# Install Brain CLI
brew install codejunkie99/tap/brain
# Check Brain status
agentic-stack brain status
# Onboard project to Brain
agentic-stack brain onboard --agents codex,cursor --yes
# Query Brain memory
agentic-stack brain ask "auth decisions"
# Write to Brain memory
agentic-stack brain note "Use PKCE for local OAuth flows."
# Get MCP command
agentic-stack brain mcp-command
Memory Transfer
# Export/import memory between projects
agentic-stack transfer
Project Structure
After installation, your project will have:
.agent/
├── memory/
│ ├── personal/PREFERENCES.md # User preferences (read first)
│ ├── semantic/ # Conceptual knowledge
│ ├── episodic/ # Session history
│ ├── working/ # Active context
│ └── .features.json # Feature toggles
├── skills/
│ ├── _manifest.jsonl # Skill registry
│ ├── brain/ # Brain integration skill
│ ├── data-layer/ # Harness monitoring
│ ├── data-flywheel/ # Training artifact export
│ ├── design-md/ # DESIGN.md workflows
│ └── tldraw/ # Visual canvas (opt-in)
├── tools/
│ └── brain_bridge.py # Brain API wrapper
├── harness/
│ └── adapters/ # Adapter-specific configs
└── install.json # Installed adapters manifest
Configuration
Initial Setup (Onboarding Wizard)
The wizard populates .agent/memory/personal/PREFERENCES.md:
# Accept all defaults (CI mode)
agentic-stack claude-code --yes
# Re-run wizard on existing project
agentic-stack claude-code --reconfigure
Wizard questions:
- What should I call you? (optional)
- Primary language(s)? (default: unspecified)
- Explanation style? (default: concise)
- Test strategy? (default: test-after)
- Commit message style? (default: conventional commits)
- Code review depth? (default: critical issues only)
Optional features (off by default):
- FTS memory search
[BETA] - tldraw visual canvas
[BETA]
Manual Preference Editing
Edit .agent/memory/personal/PREFERENCES.md directly:
---
name: Alex
languages: [Python, TypeScript]
explanation_style: detailed
test_strategy: test-first
commit_style: conventional commits
review_depth: thorough
---
# Personal Preferences
I prefer async/await over callbacks. Use descriptive variable names.
Always include error handling for network requests.
Feature Toggles
Edit .agent/memory/.features.json:
{
"fts_search": false,
"tldraw": false
}
Working with Memory Layers
Personal Memory
# View preferences
cat .agent/memory/personal/PREFERENCES.md
# Add personal context
echo "## Code Style\n\nPrefer functional composition over inheritance." >> .agent/memory/personal/PREFERENCES.md
Semantic Memory
# .agent/memory/semantic/architecture_decisions.md
"""
Document lasting project knowledge
"""
Episodic Memory
Automatically managed by harness; tracks session history and decisions.
Working Memory
Active context during current session; cleared when appropriate.
Creating Custom Skills
Skill Structure
.agent/skills/my-custom-skill/
├── SKILL.md # Main skill definition
├── README.md # Documentation
└── tools/ # Optional tool scripts
└── helper.py
SKILL.md Format
---
name: my-custom-skill
description: Does something specific for this project
version: 1.0.0
triggers:
- use my custom skill
- apply custom workflow
---
# My Custom Skill
## What It Does
Detailed explanation...
## When to Use
- Trigger condition 1
- Trigger condition 2
## Examples
\```python
# Working code example
\```
Sync Manifest After Adding Skills
agentic-stack sync-manifest
Multi-Adapter Setup
Install Multiple Harnesses
# Interactive multi-select
cd your-project
./install.sh
# Or add individually
agentic-stack add claude-code
agentic-stack add cursor
agentic-stack add windsurf
Check Installed Adapters
agentic-stack status
Output:
✓ claude-code (active)
✓ cursor (active)
✗ windsurf (not installed)
Manage via TUI
agentic-stack manage
Data Layer Usage
Generate Dashboard
# From within agent session, trigger:
# "show me the harness dashboard"
# "generate daily report"
# Or manually:
from pathlib import Path
import sys
sys.path.insert(0, str(Path.cwd() / ".agent" / "skills" / "data-layer"))
from dashboard import generate_dashboard
generate_dashboard()
View Dashboard
open .agent/data/dashboard.html
cat .agent/data/daily-report.md
Data Flywheel Usage
Export Approved Runs
from pathlib import Path
import sys
sys.path.insert(0, str(Path.cwd() / ".agent" / "skills" / "data-flywheel"))
from export import export_run
# Export specific run
export_run(
run_id="2026-05-16-auth-refactor",
redact_secrets=True,
include_context=True
)
Artifacts Generated
traces/- Execution tracescontext-cards/- Contextual summarieseval-cases/- Test cases for evaluationtraining.jsonl- Training-ready formatmetrics.json- Flywheel readiness metrics
Brain Integration
Bridge from Agent Code
#!/usr/bin/env python3
from pathlib import Path
import sys
sys.path.insert(0, str(Path.cwd() / ".agent" / "tools"))
from brain_bridge import query_brain, write_brain
# Query across projects
results = query_brain("authentication patterns")
for hit in results:
print(f"{hit['project']}: {hit['content']}")
# Write durable note
write_brain(
content="OAuth refresh tokens expire after 30 days",
tags=["auth", "security"]
)
MCP Integration
# Get MCP stdio command for harness config
agentic-stack brain mcp-command
Add to .claude/mcp.json or equivalent:
{
"mcpServers": {
"brain": {
"command": "brain",
"args": ["serve"]
}
}
}
Troubleshooting
Doctor Reports Issues
agentic-stack doctor
Common issues:
- Missing hooks: Re-run
agentic-stack add <adapter> - Orphaned files: Use
agentic-stack remove <adapter>then reinstall - Version drift: Run
agentic-stack upgrade --yes
Manifest Out of Sync
# Rebuild from installed SKILL.md files
agentic-stack sync-manifest
Python 3.9 Compatibility
Ensure Python 3.9+ is available:
python3 --version
If using brew Python:
brew install python@3.11
Migration from Pre-v0.9
# Synthesize install.json from on-disk adapters
./install.sh doctor
Brain Not Found
# Install Brain CLI first
brew install codejunkie99/tap/brain
# Verify installation
brain --version
Adapter Conflicts
# Remove conflicting adapter
agentic-stack remove cursor
# Clean reinstall
agentic-stack add cursor
Environment Variables
Common environment variables referenced:
# Optional: Custom Brain path
export BRAIN_PATH="$HOME/.config/brain"
# Optional: Override .agent directory
export AGENTIC_STACK_DIR=".agent"
Common Patterns
Single Harness Setup
cd my-project
agentic-stack claude-code
# Work exclusively in Claude Code
Multi-Harness Setup
cd my-project
agentic-stack add claude-code
agentic-stack add cursor
agentic-stack add windsurf
# Switch between tools without losing context
CI/Automation
# Scripted install (no interactive prompts)
agentic-stack claude-code --yes
# Verify installation
agentic-stack doctor || exit 1
Project Migration
# Export from old project
cd old-project
agentic-stack transfer
# Follow export prompts, save curl command
# Import to new project
cd new-project
# Paste and run curl command
Skill Development Workflow
# 1. Create skill directory
mkdir -p .agent/skills/my-skill
# 2. Write SKILL.md with frontmatter
cat > .agent/skills/my-skill/SKILL.md << 'EOF'
---
name: my-skill
description: Custom skill for X
version: 1.0.0
triggers: ["use my skill"]
---
# My Skill
...
EOF
# 3. Sync manifest
agentic-stack sync-manifest
# 4. Verify
grep "my-skill" .agent/skills/_manifest.jsonl
Safe Upgrades
# 1. Preview changes
agentic-stack upgrade --dry-run
# 2. Review output
# 3. Apply if safe
agentic-stack upgrade --yes
# 4. Verify
agentic-stack doctor
Version History Highlights
- v0.18.0: External Brain memory integration
- v0.17.0: Adapters, Mission Control, lesson retraction
- v0.16.0: Safe project upgrades via
upgradecommand - v0.12.0: tldraw visual canvas (opt-in beta)
- v0.11.0: Data layer + data flywheel
- v0.10.0: design-md skill, Python 3.9 fix
- v0.9.0: Manifest-driven harness manager
FAQ
What does the agentic-stack-portable-agent-memory skill do?
Portable .agent/ folder with memory, skills, and protocols that works across Claude Code, Cursor, Windsurf, and other AI coding harnesses
How do I install agentic-stack-portable-agent-memory?
Run npx skills add https://github.com/reason-machines/ai-agent-skills --skill agentic-stack-portable-agent-memory in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/agentic-stack-portable-agent-memory/ (personal) or .claude/skills/agentic-stack-portable-agent-memory/ (project).
Which AI agents can use agentic-stack-portable-agent-memory?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is agentic-stack-portable-agent-memory safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains agentic-stack-portable-agent-memory?
It is published by reason-machines in reason-machines/ai-agent-skills. It has 176 recorded installs.
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