aigentry-devkit

Your AI development environment, packaged.

A comprehensive development kit that bundles skills, hooks, MCP servers, HUD/statusline, and configuration templates for Claude Code, Codex CLI, and other MCP-compatible CLIs. Install once, use everywhere.

Features

Skills (Reusable AI Capabilities)

Five production-ready skills that extend Claude Code, Codex CLI, and other MCP-compatible CLIs:

• Clipboard Image Viewer - Capture and analyze clipboard images directly from your terminal
• AI Deliberation - Multi-session parallel debates across arbitrary CLI participants with structured turn-taking and synthesis
• Deliberation Executor - Convert deliberation synthesis into concrete implementation tasks and execute them
• Environment Manager - direnv-based hierarchical environment variable management with global and project-scoped variables
• YouTube Analyzer - Extract and analyze YouTube video metadata, captions, and transcripts without downloading

MCP Deliberation Server

A dedicated MCP (Model Context Protocol) server enabling multi-session AI debates with:

• Parallel deliberation sessions with independent state management
• Structured response formats (evaluation, core position, reasoning, risks, synthesis)
• Automatic session monitoring with optional tmux integration
• State persistence and session history archiving

HUD/Statusline

Custom statusline display for Claude Code that shows real-time context from stdin, with support for extended context windows (up to 1M tokens on Claude Opus).

Hooks

Session-start bootstrap hooks that automatically load skill indices and prepare your environment when Claude Code starts.

Configuration Templates

Pre-configured settings with template substitution:

• settings.json.template - Claude Code settings with {{HOME}} substitution
• global.envrc - direnv configuration for hierarchical environment management
• CLAUDE.md - AI agent instructions (oh-my-claudecode compatible)

Installation

Prerequisites

• Node.js 18+
• npm (included with Node.js)
• Optional: Claude Code CLI (npm install -g @anthropic-ai/claude-code)
• Optional: tmux (for deliberation monitoring)
• Optional: direnv (for environment management)

Quick Start

All OS (recommended):

npx --yes --package @dmsdc-ai/aigentry-devkit aigentry-devkit install

git clone is not required for this path. The npm package contains the full installer + runtime files.

Force reinstall:

npx --yes --package @dmsdc-ai/aigentry-devkit aigentry-devkit install --force

Manual install (local clone) is still available:

macOS / Linux:

git clone https://github.com/dmsdc-ai/aigentry-devkit.git
cd aigentry-devkit
bash install.sh

Windows (PowerShell):

git clone https://github.com/dmsdc-ai/aigentry-devkit.git
cd aigentry-devkit
powershell -ExecutionPolicy Bypass -File .\install.ps1

The installer will:

1. Verify Node.js and optional dependencies (Claude Code CLI, tmux, direnv)
2. Install skills to ~/.claude/skills/
3. Install HUD statusline to ~/.claude/hud/
4. Set up full MCP Deliberation runtime at ~/.local/lib/mcp-deliberation/ (server + browser adapters + selectors + monitor)
5. Register MCP server in ~/.claude/.mcp.json
6. Create configuration templates from templates
7. Attempt Codex CLI integration (if available)
8. Print cross-platform browser scan/fallback notes

Post-Installation

After installation, restart Claude/Codex for changes to take effect:

# Restart your CLI process to load new MCP settings

To verify installation:

ls -la ~/.claude/skills/      # Check skills are installed
ls -la ~/.claude/hud/         # Check HUD is installed
ls -la ~/.local/lib/mcp-deliberation/  # Check MCP server
ls -la ~/.local/lib/mcp-deliberation/selectors/  # Check browser selector assets
cat ~/.claude/.mcp.json       # Verify MCP registration

Usage

Skills

Skills are automatically available in Claude Code, Codex CLI, and compatible MCP clients. They activate based on keywords:

Clipboard Image

Triggers: "clipboard", "paste image", "캡처 확인"

View and analyze images from your clipboard:

"Analyze this screenshot: [image in clipboard]"
"What's on my clipboard?"

AI Deliberation

Triggers: "deliberation", "토론", "debate", "deliberate"

Start a multi-perspective debate:

"deliberation: Should we use microservices or monolith?"
"토론 시작: API 설계 전략"

Multiple sessions run in parallel. Use deliberation_start to get a session ID, then reference it in subsequent calls.

Deliberation Executor

Triggers: "합의안 구현", "토론 결과 구현", "deliberation 구현", "synthesis 구현", "executor"

Execute implementation from synthesis:

"session_id abc123 합의안 구현해줘"
"토론 결과를 코드로 반영하고 테스트까지 진행해줘"

Use this after deliberation_synthesize when you want implementation, not just discussion.

Environment Manager

Triggers: "env", "환경변수", "environment", ".env", "direnv"

Manage environment variables hierarchically:

"env check" - Audit environment setup
"env init /path/to/project" - Initialize new project
"env add API_KEY value" - Add global or project variable

YouTube Analyzer

Triggers: "youtube", "유튜브", "영상 분석", "video analysis"

Extract and analyze YouTube content:

"Analyze this video: https://youtube.com/watch?v=xxx"
"유튜브 영상 요약: https://youtu.be/xxx"

MCP Deliberation Server

The deliberation server provides these tools:

| Tool | Purpose | |------|---------| | deliberation_speaker_candidates | List selectable speakers from local CLIs and open browser LLM tabs | | deliberation_start | Start new debate session with user-selected speakers, returns session_id (participant_types override supported) | | deliberation_route_turn | Resolve current speaker transport and next action (cli_respond / clipboard / browser_auto) | | deliberation_browser_auto_turn | Send turn to browser LLM automatically via CDP and collect response | | deliberation_respond | Submit turn response | | deliberation_browser_llm_tabs | Inspect open browser LLM tabs | | deliberation_clipboard_prepare_turn | Copy current-turn prompt for browser LLM | | deliberation_clipboard_submit_turn | Submit clipboard/browser response as a turn | | deliberation_context | Load project context | | deliberation_list_active | List active sessions | | deliberation_status | Check session status | | deliberation_synthesize | Generate synthesis report | | deliberation_history | View full debate transcript | | deliberation_list | Browse past sessions | | deliberation_reset | Clear sessions |

Example workflow:

# Start any CLI with MCP deliberation enabled
<your-cli>

# In CLI A:
# > "deliberation: API design - REST vs GraphQL?"
# 1) Find selectable participants (CLI + browser LLM tabs)
# deliberation_speaker_candidates()
# 2) Start with manually selected speakers
# deliberation_start(topic="...", speakers=["codex","web-claude-1","web-chatgpt-1"], first_speaker="codex")
# optional: force transport profile per speaker
# deliberation_start(topic="...", speakers=["codex","chatgpt"], participant_types={"chatgpt":"browser_auto"})
# 3) Route the current turn
# deliberation_route_turn session_id=sess_12345
# Submit turns with deliberate speakers:
# deliberation_respond session_id=sess_12345 speaker=codex
# Browser turn flow:
# deliberation_clipboard_prepare_turn session_id=sess_12345 speaker=web-claude-1
# (paste into browser LLM, copy response)
# deliberation_clipboard_submit_turn session_id=sess_12345 speaker=web-claude-1
# Browser auto flow (CDP):
# deliberation_browser_auto_turn session_id=sess_12345 provider=chatgpt
# After rounds complete:
# deliberation_synthesize session_id=sess_12345

HUD Statusline

The simple-status.sh script displays context in your shell prompt. Configure in ~/.claude/settings.json:

{
  "hud": {
    "enabled": true,
    "script": "~/.claude/hud/simple-status.sh",
    "contextWindow": 1000000
  }
}

Project Structure

aigentry-devkit/
├── bin/                     # npx entrypoint
│   └── aigentry-devkit.js
├── .claude-plugin/           # Claude Code plugin manifests
│   ├── plugin.json          # Plugin metadata
│   └── marketplace.json     # Marketplace listing
├── config/                  # Configuration templates
│   ├── CLAUDE.md            # AI agent instructions
│   ├── settings.json.template
│   └── envrc/global.envrc
├── hooks/                   # Session lifecycle hooks
│   ├── hooks.json           # Hook definitions
│   └── session-start        # Bootstrap script
├── hud/                     # Statusline/HUD
│   └── simple-status.sh
├── mcp-servers/             # Model Context Protocol servers
│   └── deliberation/        # AI deliberation server
│       ├── index.js         # Main server implementation
│       ├── package.json
│       └── session-monitor.sh
├── skills/                  # Reusable AI skills
│   ├── clipboard-image/     # Image clipboard capture
│   ├── deliberation/        # Debate management
│   ├── deliberation-executor/ # Synthesis-to-implementation execution
│   ├── env-manager/         # Environment variables
│   └── youtube-analyzer/    # YouTube content analysis
├── install.sh               # Installation script (macOS/Linux)
├── install.ps1              # Installation script (Windows PowerShell)
├── package.json             # npm package metadata (@dmsdc-ai/aigentry-devkit)
├── LICENSE                  # MIT License
└── README.md                # This file

Configuration

Claude Code Integration

After installation, skills and MCP servers are automatically available. Configuration is stored in:

• ~/.claude/skills/ - Skill definitions
• ~/.claude/.mcp.json - MCP server registration
• ~/.claude/settings.json - Claude Code settings

Codex CLI Integration

If Codex CLI is installed, the installer attempts to register the MCP deliberation server. Manual registration:

codex mcp add deliberation -- node ~/.local/lib/mcp-deliberation/index.js

Important: Codex is a participant CLI in deliberation, not a separate MCP server you must install.

Other CLIs can join deliberation by registering the same MCP server command in their MCP/client configuration:

node ~/.local/lib/mcp-deliberation/index.js

Environment Management

direnv integration (requires direnv):

# Global configuration
cp config/envrc/global.envrc ~/.envrc
direnv allow

# Per-project
cd ~/my-project
echo 'source_up_if_exists' > .envrc
echo 'dotenv_if_exists .env.local' >> .envrc
direnv allow

Troubleshooting

Skills not loading

1. Verify skills are installed: ls -la ~/.claude/skills/
2. Restart your MCP client process (Claude/Codex/etc.)
3. Check for keyword matches in skill definitions

MCP Deliberation not available

1. Verify MCP registration: cat ~/.claude/.mcp.json
2. Check installation: ls ~/.local/lib/mcp-deliberation/
3. Reinstall runtime files: npx --yes --package @dmsdc-ai/aigentry-devkit aigentry-devkit install --force
4. Restart your MCP client process (Claude/Codex/etc.)
5. Review runtime log: tail -n 120 ~/.local/lib/mcp-deliberation/runtime.log

MCP Transport closed in multi-session use

1. Restart the current CLI session first (stdio transport is session-bound).
2. Avoid killing deliberation with pkill -f mcp-deliberation; this can terminate other active sessions.
3. Keep one active CLI tab per long-running deliberation workflow when possible.
4. Check runtime log: tail -n 120 ~/.local/lib/mcp-deliberation/runtime.log
5. Confirm lock directory exists: ls ~/.local/lib/mcp-deliberation/state/<project>/.locks

Multi-session stability in v2.4 uses:

• Session/project lock files (.locks/) to serialize writes
• Atomic file writes for session/markdown persistence
• Safe tool handlers + uncaught error logging to keep server process alive

Browser LLM tabs not detected (Linux/Windows)

Browser tab scan is cross-platform, but Linux/Windows rely on CDP endpoints. Start your browser with a remote debugging port:

Linux/macOS:

google-chrome --remote-debugging-port=9222

Windows (PowerShell):

& "$Env:ProgramFiles\Google\Chrome\Application\chrome.exe" --remote-debugging-port=9222

Then run:

deliberation_browser_llm_tabs

If auto-scan is still unavailable, use the clipboard fallback:

• deliberation_clipboard_prepare_turn
• paste into browser LLM and copy response
• deliberation_clipboard_submit_turn

Environment variables not loading

1. Check direnv installation: command -v direnv
2. Verify .envrc files: cat ~/.envrc and cat ~/project/.envrc
3. Allow the directory: direnv allow
4. Test: direnv exec /bin/bash 'echo $VARIABLE_NAME'

YouTube Analyzer errors

1. Verify Python 3.8+: python3 --version
2. Check yt-dlp: python3 -c "import yt_dlp; print('OK')"
3. Install if missing: pip install yt-dlp

Development

Adding new skills

1. Create directory: skills/my-skill/
2. Add SKILL.md with metadata and implementation
3. Reinstall: bash install.sh --force

Customizing MCP server

Edit mcp-servers/deliberation/index.js and reinstall:

cd ~/.local/lib/mcp-deliberation
npm install

Extending configuration

Add templates to config/ and update both install.sh and install.ps1 to deploy them.

Requirements

• Node.js: 18+ (for MCP server)
• npm: Latest (included with Node.js)
• Claude Code CLI: v1.0+ (optional, for full integration)
• Codex CLI: Latest (optional, for Codex integration)
• tmux: Latest (optional, for deliberation monitoring)
• direnv: Latest (optional, for environment management)
• PowerShell: 7+ recommended on Windows

Language-specific requirements for skills:

• YouTube Analyzer: Python 3.8+, yt-dlp
• Clipboard Image: xclip or pbpaste (platform-dependent)

Architecture

Installation Flow

npx --yes --package @dmsdc-ai/aigentry-devkit aigentry-devkit install
  ├─ dispatches to install.sh (macOS/Linux) or install.ps1 (Windows)
  ├─ Check prerequisites (Node.js, npm, optional tools)
  ├─ Install skills to ~/.claude/skills/
  ├─ Install HUD to ~/.claude/hud/
  ├─ Deploy MCP server to ~/.local/lib/mcp-deliberation/
  ├─ Register MCP in ~/.claude/.mcp.json
  ├─ Create config from templates (settings.json, .envrc)
  └─ Integrate with Codex CLI (if available)

Runtime Flow

MCP Client Start (Claude/Codex/others)
  ├─ Load plugins from .claude-plugin/
  ├─ Execute SessionStart hooks
  │  └─ Run hooks/session-start (load skill index)
  ├─ Register MCP servers from ~/.claude/.mcp.json
  │  └─ Connect to MCP Deliberation Server
  ├─ Load skills from ~/.claude/skills/
  └─ Ready for interaction

Skill Activation

User message with keywords
  ├─ Match against skill trigger patterns
  ├─ Load appropriate skill SKILL.md
  ├─ Execute skill workflow
  └─ Return results

Performance

• Skills load on-demand (no performance impact until triggered)
• MCP server runs in separate process (non-blocking)
• direnv setup is cached after first load
• HUD statusline updates asynchronously

Compatibility

| Tool | Supported | Tested | |------|-----------|--------| | Claude Code | 1.0+ | Yes | | Codex CLI | Latest | Yes | | Node.js | 18+ | 20 LTS, 22 | | macOS | Ventura+ | Yes | | Linux | Ubuntu 22.04+ | Yes | | Windows | 10/11 + PowerShell | Yes |

Contributing

Contributions welcome. Please follow these guidelines:

1. Test skills locally before submitting
2. Update SKILL.md documentation
3. Ensure installer remains idempotent
4. Follow existing code style

License

MIT License - See LICENSE file for details.

Copyright 2026 dmsdc-ai

Support

• Report issues: GitHub Issues
• Documentation: GitHub Wiki
• Community: dmsdc-ai Organization

Acknowledgments

Built with:

• Claude Code by Anthropic
• Model Context Protocol by Anthropic
• oh-my-claudecode - Multi-agent orchestration framework

aigentry-devkit - Streamline your AI development workflow.