uroma 8014ad0bcc Fix Docker tests to achieve 100% on 2/3 installation methods
Major fixes:
- Fixed Claude Code verification (was checking 'claude-code', now checks 'claude')
- Fixed volume mount paths (use absolute path /tmp/claude-repo for runtime)
- Fixed agents copy path (removed incorrect /agents/ subdirectory)
- Fixed critical agent paths (studio-coach in bonus/, not project-management)
- Added expect package for interactive installer automation
- Fixed test count aggregation to read from individual result files

Test Results (after fixes):
 Manual Installation: 27/27 passing (100%)
 Master Prompt Installation: 15/15 passing (100%)
⚠️  Interactive Installer: 7/13 passing (54% - expect automation issue)

Note: Interactive installer works fine for manual testing, just difficult
to automate with expect scripts due to prompt matching complexity.
8014ad0bcc · 2026-01-16 10:54:31 +00:00
42 Commits

🚀 Ultimate Claude Code & GLM Suite

40+ specialized AI agents, 15+ MCP tools, 7 PROACTIVELY auto-triggering coordinators for Claude Code. Works with Anthropic Claude and Z.AI/GLM models (90% cost savings).

💡 Tip: Use invite token R0K78RJKNW for 10% OFF Z.AI GLM Plan subscription: https://z.ai/subscribe?ic=R0K78RJKNW

Agents PROACTIVELY MCP Tools License


🎯 What's New (January 2026)

Latest Updates

  • 📊 Agent Coordination System - 7 PROACTIVELY coordinators automatically orchestrate 31 specialists
  • 🎨 ui-ux-pro-max Integration - Professional UI/UX agent with 50+ styles, 97 palettes, WCAG compliance
  • 📝 MASTER-PROMPT.md Enhanced - Complete workflow examples, proper markdown formatting
  • 🔧 All 7 Coordinators Documented - studio-coach, ui-ux-pro-max, whimsy-injector, test-writer-fixer, experiment-tracker, studio-producer, project-shipper
  • 📚 Complete Documentation - Workflow examples, coordination patterns, real-world use cases

🏗️ Architecture Overview

38 Total Agents = 7 Coordinators + 31 Specialists

The 7 PROACTIVELY coordinators auto-trigger based on context and orchestrate specialists automatically:

Coordinator Department Auto-Triggers On
ui-ux-pro-max Design UI/UX design work, components, pages
whimsy-injector Design After UI/UX changes for delightful touches
test-writer-fixer Engineering After code modifications for testing
experiment-tracker Project Management Feature flags, A/B tests, experiments
studio-producer Project Management Cross-team coordination, resource conflicts
project-shipper Project Management Launches, releases, go-to-market activities
studio-coach Bonus Complex multi-agent tasks, agent confusion

How It Works:

  • Automatic Path: Coordinators auto-trigger → call specialists → coordinate workflow
  • Manual Path: You directly invoke any specialist for precise control
  • Best of Both: Automation when you want it, control when you need it

Real Example:

You: "I need a viral TikTok app in 2 weeks"
      ↓
[studio-coach PROACTIVELY triggers]
      ↓
Coordinates: rapid-prototyper + tiktok-strategist + frontend-developer
      ↓
[whimsy-injector PROACTIVELY triggers]
      ↓
Adds delightful touches
      ↓
[project-shipper PROACTIVELY triggers]
      ↓
Plans launch strategy
      ↓
Result: Complete app, launch-ready ✓

🚀 Quick Start

# Clone the repository
git clone https://github.rommark.dev/admin/claude-code-glm-suite.git
cd claude-code-glm-suite

# Run the interactive installer
chmod +x interactive-install-claude.sh
./interactive-install-claude.sh

# Follow the prompts:
# ✅ Choose model (Anthropic/Z.AI)
# ✅ Select agent categories to install
# ✅ Configure MCP tools
# ✅ Enter your API key
# ✅ Launch Claude Code

⚠️ IMPORTANT: For Z.AI / GLM Users

If using the GLM Coding Plan (90% cheaper), you MUST configure GLM FIRST before using Claude Code!

🎯 EASIEST METHOD - Use Z.AI Coding Helper Wizard:

# Install coding helper and run setup wizard
npm install -g @z_ai/coding-helper
npx @z_ai/coding-helper init

# The wizard will:
# ✅ Ask for your Z.AI API key
# ✅ Configure Claude Code for GLM automatically
# ✅ Set up model mappings (glm-4.5-air, glm-4.7)
# ✅ Verify everything works

# Start Claude Code with GLM
claude

Manual Configuration (if you prefer):

# Get API key: https://z.ai/
mkdir -p ~/.claude
cat > ~/.claude/settings.json << 'EOF'
{
  "env": {
    "ANTHROPIC_AUTH_TOKEN": "YOUR_ZAI_API_KEY_HERE",
    "ANTHROPIC_BASE_URL": "https://api.z.ai/api/anthropic",
    "API_TIMEOUT_MS": "3000000",
    "ANTHROPIC_DEFAULT_HAIKU_MODEL": "glm-4.5-air",
    "ANTHROPIC_DEFAULT_SONNET_MODEL": "glm-4.7",
    "ANTHROPIC_DEFAULT_OPUS_MODEL": "glm-4.7"
  }
}
EOF
npm install -g @anthropic-ai/claude-code
claude

📋 Installation Options

Copy and paste into Claude Code - it will guide you through the entire installation step-by-step:

📄 MASTER-PROMPT.md

Quick Start:

  1. If using GLM: Configure GLM first (see above)
  2. Start Claude Code: claude
  3. Copy the prompt from MASTER-PROMPT.md (clearly marked with ✂️ COPY FROM HERE)
  4. Paste into Claude Code
  5. Done!

Benefits:

  • See all steps before executing
  • Easy to customize and understand
  • Works entirely within Claude Code
  • Includes all source repository references

Option 2: Interactive Installation Script

git clone https://github.rommark.dev/admin/claude-code-glm-suite.git
cd claude-code-glm-suite
chmod +x interactive-install-claude.sh
./interactive-install-claude.sh

Benefits:

  • Automated execution
  • Menu-driven configuration
  • Backup and verification built-in
  • Faster for experienced users

Option 3: Manual Installation

For users who want complete control over each component, follow these steps manually:

Prerequisites

Required:

  • Node.js 14+ and npm
  • Python 3 (optional, for some MCP tools)
  • Claude Code installed: npm install -g @anthropic-ai/claude-code

Step 1: Configure Claude Code

For Anthropic Claude:

mkdir -p ~/.claude
cat > ~/.claude/settings.json << 'EOF'
{
  "env": {
    "ANTHROPIC_AUTH_TOKEN": "sk-ant-your-api-key-here",
    "ANTHROPIC_BASE_URL": "https://api.anthropic.com"
  }
}
EOF

For Z.AI / GLM (90% cheaper):

npm install -g @z_ai/coding-helper
npx @z_ai/coding-helper init
# Follow the wizard to configure GLM

Step 2: Install Agents (38 agents with PROACTIVELY auto-triggering)

# Clone the agents repository
git clone https://github.com/contains-studio/agents.git /tmp/contains-studio-agents

# Copy all agents to Claude Code
mkdir -p ~/.claude/agents
cp -r /tmp/contains-studio-agents/agents/* ~/.claude/agents/

# Verify
find ~/.claude/agents -name "*.md" | wc -l
# Should show 39 files (38 agents + README)

Step 3: Install MCP Tools

# Install vision and analysis tools
npm install -g @z_ai/mcp-server

# Install web search and GitHub integration
npm install -g @z_ai/coding-helper

# Install TLDR for token-efficient code analysis
npm install -g llm-tldr

# Verify
npx @z_ai/mcp-server --help
npx @z_ai/coding-helper --help
tldr --help

Step 4: Install UI/UX Pro Max Skill

# Clone the skill repository
git clone https://github.com/nextlevelbuilder/ui-ux-pro-max-skill.git /tmp/ui-ux-skill

# Copy to Claude skills directory
mkdir -p ~/.claude/skills
cp -r /tmp/ui-ux-skill/* ~/.claude/skills/

Step 5: Configure MCP Tools

# Create MCP configuration
cat > ~/.claude/settings.local.json << 'EOF'
{
  "mcpServers": {
    "zai-vision": {
      "command": "npx",
      "args": ["@z_ai/mcp-server"]
    },
    "zai-web": {
      "command": "npx",
      "args": ["@z_ai/coding-helper"]
    }
  }
}
EOF

Step 6: Install Ralph CLI (Advanced - Optional)

⚠️ Optional: Ralph CLI provides autonomous agent looping with background execution. Skip if not needed.

# Install Ralph CLI
npm install -g @iannuttall/ralph

# Create auto-trigger hook
mkdir -p ~/.claude/hooks
cat > ~/.claude/hooks/ralph-auto-trigger.sh << 'EOF'
#!/bin/bash
# Ralph Auto-Trigger Hook - Background Spawning
# (Full script in MASTER-PROMPT.md Step 6)
CLAUDE_DIR="$HOME/.claude"
RALPH_PID_FILE="$CLAUDE_DIR/ralph.pid"
RALPH_LOG_FILE="$CLAUDE_DIR/ralph-output.log"
RALPH_LOCK_FILE="$CLAUDE_DIR/ralph.lock"
RALPH_AUTO_MODE="${RALPH_AUTO_MODE:-agents}"
RALPH_MAX_ITERATIONS="${RALPH_MAX_ITERATIONS:-50}"

# Read input
HOOK_INPUT=$(cat)
USER_PROMPT=$(echo "$HOOK_INPUT" | jq -r '.prompt // empty' 2>/dev/null || echo "")

# Check if already running
if [[ -f "$RALPH_LOCK_FILE" ]]; then
    LOCK_PID=$(cat "$RALPH_LOCK_FILE" 2>/dev/null || echo "")
    if [[ -n "$LOCK_PID" ]] && kill -0 "$LOCK_PID" 2>/dev/null; then
        exit 0
    else
        rm -f "$RALPH_LOCK_FILE" "$RALPH_PID_FILE"
    fi
fi

# Detect agent request
AGENTS=("ai-engineer" "backend-architect" "devops-automator" "frontend-developer" "mobile-app-builder" "rapid-prototyper" "test-writer-fixer" "tiktok-strategist" "growth-hacker" "content-creator" "instagram-curator" "reddit-builder" "twitter-engager" "app-store-optimizer" "brand-guardian" "ui-designer" "ux-researcher" "visual-storyteller" "whimsy-injector" "ui-ux-pro-max" "feedback-synthesizer" "sprint-prioritizer" "trend-researcher" "experiment-tracker" "project-shipper" "studio-producer" "studio-coach" "analytics-reporter" "finance-tracker" "infrastructure-maintainer" "legal-compliance-checker" "support-responder" "api-tester" "performance-benchmarker" "test-results-analyzer" "tool-evaluator" "workflow-optimizer" "joker" "agent-updater" "explore" "plan" "general-purpose")

agent_detected=false
detected_agent=""
for agent in "${AGENTS[@]}"; do
    if echo "$USER_PROMPT" | grep -iq "$agent"; then
        agent_detected=true
        detected_agent="$agent"
        break
    fi
done

# Should trigger?
should_trigger=false
case "$RALPH_AUTO_MODE" in
    "always") should_trigger=true ;;
    "agents")
        if [[ "$agent_detected" == true ]] || echo "$USER_PROMPT" | grep -qiE "build|create|implement|develop|fix|add|refactor|optimize|write|generate|delegate|autonomous"; then
            should_trigger=true
            [[ "$agent_detected" == false ]] && detected_agent="general-development"
        fi
        ;;
esac

if [[ "$should_trigger" == true ]] && command -v ralph &> /dev/null; then
    mkdir -p "$CLAUDE_DIR"
    cat > "$CLAUDE_DIR/ralph-loop.local.md" << STATEEOF
# Ralph Loop State - Auto-Triggered
**User Request:** $USER_PROMPT
**Detected Agent:** $detected_agent
**Mode:** $RALPH_AUTO_MODE
STATEEOF

    touch "$RALPH_LOG_FILE"
    echo "[$(date -u +"%Y-%m-%d %H:%M:%S UTC")] Starting Ralph in background..." >> "$RALPH_LOG_FILE"
    nohup ralph build "$RALPH_MAX_ITERATIONS" >> "$RALPH_LOG_FILE" 2>&1 &
    RALPH_PID=$!
    echo "$RALPH_PID" > "$RALPH_PID_FILE"
    echo "$RALPH_PID" > "$RALPH_LOCK_FILE"
    echo "🔄 Ralph CLI auto-started in background (PID: $RALPH_PID)" >&2
fi
exit 0
EOF

chmod +x ~/.claude/hooks/ralph-auto-trigger.sh

# Configure hooks
cat > ~/.claude/hooks.json << 'EOF'
{
  "description": "User hooks for Ralph auto-trigger",
  "hooks": {
    "UserPromptSubmit": [
      {
        "type": "command",
        "command": "bash",
        "args": ["~/.claude/hooks/ralph-auto-trigger.sh", "{{userPrompt}}"]
      }
    ]
  }
}
EOF

Configure Ralph environment:

# Add to your shell profile (~/.bashrc or ~/.zshrc)
export RALPH_AUTO_MODE="agents"  # Options: agents, always, off
export RALPH_MAX_ITERATIONS="50"

Step 7: Verify Installation

# Check agents
find ~/.claude/agents -name "*.md" | wc -l
# Should show 39

# Check MCP tools
npx @z_ai/mcp-server --help
npx @z_ai/coding-helper --help

# Check Ralph (if installed)
ralph --version
ls -la ~/.claude/hooks/ralph-auto-trigger.sh

# Start Claude Code
claude

What's Included

  • 🤖 38 Custom Agents across 8 departments
    • 7 PROACTIVELY coordinators that auto-trigger and orchestrate specialists
    • 31 specialist agents for domain-specific tasks
  • 🔧 15+ MCP Tools for vision, search, and GitHub integration
  • 🤖 Ralph CLI Integration (Advanced) - Autonomous agent looping with background execution
  • Intelligent Coordination - Coordinators automatically detect context and orchestrate workflows
  • 🎛️ Interactive Installation with model selection (Anthropic/Z.AI)
  • 🛡️ One-Click Setup with comprehensive verification
  • 📚 Complete Documentation with real-world workflow examples

🤖 Agent Departments

Engineering (7 agents)

  • AI Engineer - ML & LLM integration, prompt engineering
  • Backend Architect - API design, database architecture, microservices
  • DevOps Automator - CI/CD pipelines, infrastructure as code
  • Frontend Developer - React/Vue/Angular, responsive design
  • Mobile Builder - iOS/Android React Native apps
  • Rapid Prototyper - Quick MVPs in 6-day cycles
  • Test Writer/Fixer - Auto-write and fix tests (PROACTIVELY)

Design (6 agents)

  • UI/UX Pro Max - Professional UI/UX design with 50+ styles, 97 palettes, WCAG (PROACTIVELY)
  • Whimsy Injector - Delightful micro-interactions and memorable UX (PROACTIVELY)
  • Brand Guardian - Brand consistency
  • UI Designer - UI design and implementation
  • UX Researcher - User experience research
  • Visual Storyteller - Visual communication

Project Management (3 agents)

  • Experiment Tracker - A/B test tracking and metrics (PROACTIVELY)
  • Project Shipper - Launch coordination and go-to-market (PROACTIVELY)
  • Studio Producer - Cross-team coordination and resources (PROACTIVELY)

Product (3 agents)

  • Feedback Synthesizer - User feedback analysis
  • Sprint Prioritizer - 6-day sprint planning
  • Trend Researcher - Market trend analysis

Marketing (7 agents)

  • TikTok Strategist - Viral TikTok marketing strategies
  • Growth Hacker - Growth strategies and user acquisition
  • Content Creator - Multi-platform content creation
  • Instagram Curator - Instagram strategy and engagement
  • Reddit Builder - Reddit community building
  • Twitter Engager - Twitter strategy and tactics
  • App Store Optimizer - ASO optimization

Studio Operations (5 agents)

  • Analytics Reporter - Data analysis and reporting
  • Finance Tracker - Financial tracking
  • Infrastructure Maintainer - Infrastructure management
  • Legal Compliance Checker - Compliance checks
  • Support Responder - Customer support automation

Testing (5 agents)

  • API Tester - API testing
  • Performance Benchmarker - Performance testing
  • Test Results Analyzer - Test analysis
  • Tool Evaluator - Tool evaluation
  • Workflow Optimizer - Workflow optimization

Bonus (2 agents)

  • Studio Coach - Team coaching and motivation for complex tasks (PROACTIVELY)
  • Joker - Humor and team morale

🎯 PROACTIVELY Auto-Coordination

How It Works

The 7 PROACTIVELY coordinators automatically orchestrate the 31 specialists based on context:

Two Pathways:

  1. Automatic (Recommended)

    • Coordinators auto-trigger based on context
    • Call appropriate specialists
    • Coordinate multi-agent workflows
    • Ensure quality and completeness
  2. Direct

    • Manually invoke any specialist
    • Precise control over specific tasks
    • Use when you need specific expertise

The 7 PROACTIVELY Coordinators

1. ui-ux-pro-max (Design)

Triggers on: UI/UX design work, components, pages, dashboards

Provides:

  • Professional design patterns
  • 50+ design styles (glassmorphism, minimalism, brutalism, etc.)
  • 97 color palettes by industry
  • 57 font pairings with Google Fonts
  • WCAG 2.1 AA/AAA accessibility compliance
  • Tech-stack specific patterns (React, Next.js, Vue, Tailwind, shadcn/ui)

2. whimsy-injector (Design)

Triggers after: UI/UX changes, new components, feature completion

Provides:

  • Delightful micro-interactions
  • Memorable user moments
  • Playful animations
  • Engaging empty states
  • Celebratory success states

3. test-writer-fixer (Engineering)

Triggers after: Code modifications, refactoring, bug fixes

Provides:

  • Comprehensive test coverage
  • Unit, integration, and E2E tests
  • Failure analysis and repair
  • Test suite health maintenance
  • Edge case coverage

4. experiment-tracker (Project Management)

Triggers on: Feature flags, A/B tests, experiments, product decisions

Provides:

  • Experiment design and setup
  • Success metrics definition
  • A/B test tracking
  • Statistical significance calculation
  • Data-driven decision support

5. studio-producer (Project Management)

Triggers on: Team collaboration, resource conflicts, workflow issues

Provides:

  • Cross-team coordination
  • Resource allocation optimization
  • Workflow improvement
  • Dependency management
  • Sprint planning support

6. project-shipper (Project Management)

Triggers on: Releases, launches, go-to-market, shipping milestones

Provides:

  • Launch planning and coordination
  • Release calendar management
  • Go-to-market strategy
  • Stakeholder communication
  • Post-launch monitoring

7. studio-coach (Bonus)

Triggers on: Complex projects, multi-agent tasks, agent confusion

Provides:

  • Elite performance coaching
  • Multi-agent coordination
  • Motivation and alignment
  • Problem-solving guidance
  • Best practices enforcement

Real Workflow Example

You: "I need a viral TikTok app in 2 weeks"
      ↓
[studio-coach PROACTIVELY triggers]
      ↓
Analyzes complexity and coordinates:
  → rapid-prototyper builds MVP
  → tiktok-strategist plans viral features
  → frontend-developer builds UI
      ↓
[whimsy-injector PROACTIVELY triggers]
      ↓
Adds delightful touches and micro-interactions
      ↓
[project-shipper PROACTIVELY triggers]
      ↓
Plans launch strategy and coordinates release
      ↓
Result: Complete viral app, launch-ready, in 2 weeks ✓

Key Benefits:

  • No manual orchestration required
  • Automatic quality gates (testing, UX, launches)
  • Intelligent specialist selection
  • Seamless multi-agent workflows
  • Consistent delivery quality

🤖 Ralph CLI Integration (Advanced)

🔗 Source: @iannuttall/ralph

⚠️ Advanced Feature: Ralph CLI provides autonomous agent looping for complex, multi-hour development sessions. It's optional but powerful for "fire and forget" workflows.

What Ralph CLI Does

PROACTIVELY Agents = Quick coordination (single interaction) Ralph CLI = Autonomous looping (multi-iteration, background execution)

Ralph CLI runs in the background (non-blocking), allowing you to continue working in Claude Code while it autonomously completes complex tasks.

How It Works

1. You request: "Build a TikTok app in 2 weeks"
      ↓
2. Hook detects agent request
      ↓
3. Hook spawns Ralph in BACKGROUND (non-blocking)
      ↓
4. Claude Code immediately continues ← You keep working!
      ↓
5. Ralph autonomously loops in background:
   - Iteration 1: rapid-prototyper builds MVP
   - Iteration 2: tiktok-strategist plans viral features
   - Iteration 3: frontend-developer builds UI
   - Continues until complete or max iterations reached
      ↓
6. Monitor Ralph: tail -f ~/.claude/ralph-output.log

Key Features

Feature Description
Background Execution Runs as background process (NON-BLOCKING)
Auto-Spawning Hook automatically starts Ralph when needed
Process Tracking PID file for monitoring and control
Lock Mechanism Prevents duplicate Ralph instances
Real-time Logging Monitor progress: tail -f ~/.claude/ralph-output.log
Persistent State State preserved in ~/.claude/ralph-loop.local.md

Control Modes

# Mode 1: Auto-start only for agent requests (default)
export RALPH_AUTO_MODE="agents"

# Mode 2: Auto-start for everything
export RALPH_AUTO_MODE="always"

# Mode 3: Disable auto-start
export RALPH_AUTO_MODE="off"

# Set max iterations (default: 50)
export RALPH_MAX_ITERATIONS="100"

Monitoring & Control

# Monitor Ralph's output in real-time
tail -f ~/.claude/ralph-output.log

# Check if Ralph is running
cat ~/.claude/ralph.pid

# Stop Ralph manually
kill $(cat ~/.claude/ralph.pid)
rm ~/.claude/ralph.lock

# View trigger history
cat ~/.claude/ralph-trigger.log

Real-Life Example

Scenario: You need to build a complex feature while handling other tasks.

You: "Use the ai-engineer to implement a machine learning pipeline"

[Hook triggers automatically]

🔄 Ralph CLI auto-started in background
   PID: 12345
   Agent: ai-engineer
   Monitor: tail -f ~/.claude/ralph-output.log

Claude: "I've delegated the ML pipeline to Ralph, which is now
         working autonomously in the background (20-30 min expected).
         I'm still available to help with other tasks!"

You: "Perfect. While Ralph works on the ML pipeline, can you help me
       write unit tests for the authentication module?"

Claude: "Absolutely! Let's write those tests..."
[You work on tests while Ralph builds the ML pipeline in background]

Ralph vs PROACTIVELY Agents

Feature Ralph CLI (Background) PROACTIVELY Agents
Execution Multi-loop, background Single interaction
Blocking NON-BLOCKING Blocking (waits)
State File + log Context only
Control Manual stop (PID) Automatic completion
Best For Large projects, overnight Quick tasks, collaboration

Installation

Ralph CLI is available as an optional installation step in both:

  • MASTER-PROMPT.md (Step 6)
  • interactive-install-claude.sh (Step 6: Ralph CLI Selection)

To install:

npm install -g @iannuttall/ralph

To enable auto-trigger:

# The installer creates the hook automatically
# Or manually: Follow Step 6 in MASTER-PROMPT.md

When to Use Ralph CLI

Use Ralph CLI for:

  • Complex multi-step projects (2+ hours)
  • "Fire and forget" autonomous coding
  • Overnight builds/refactors
  • Large-scale refactoring
  • Multi-feature implementations

Use PROACTIVELY agents for:

  • Quick tasks (minutes)
  • Human collaboration needed
  • Design discussions
  • Code reviews
  • Quick fixes

You can use BOTH together - Set RALPH_AUTO_MODE="agents" for a hybrid approach where Ralph assists with big tasks while PROACTIVELY agents handle quick coordination.


🔧 MCP Tools

Vision Tools (8 tools)

Tool Function Input
analyze_image General image analysis PNG, JPG, JPEG
analyze_video Video content analysis MP4, MOV, M4V
ui_to_artifact UI screenshot to code Screenshots
extract_text OCR text extraction Any image
diagnose_error Error screenshot diagnosis Error screenshots
ui_diff_check Compare UI screenshots Before/after
analyze_data_viz Data visualization insights Dashboards, charts
understand_diagram Technical diagram analysis UML, flowcharts

Web & GitHub Tools

Tool Function Source
web-search-prime AI-optimized web search Real-time information
web-reader Web page to markdown conversion Documentation access
zread GitHub repository reader Codebase analysis
@z_ai/mcp-server Vision and analysis tools @z_ai/mcp-server
@z_ai/coding-helper Web and GitHub integration @z_ai/coding-helper

📚 Documentation


📖 Complete Source Guide

This suite integrates 7 major open-source projects:

1. contains-studio/agents 🎭

Source: https://github.com/contains-studio/agents Provides: 38 specialized agents with PROACTIVELY auto-triggering Key Innovation: Context-aware agent selection system

2. @z_ai/mcp-server 🖼️

Source: https://github.com/zai-ai/mcp-server Provides: 8 vision tools for images, videos, diagrams Key Feature: Understand visual content for debugging and design

3. @z_ai/coding-helper 🌐

Source: https://github.com/zai-ai/mcp-server Provides: Web search, GitHub integration, GLM setup wizard Key Feature: Interactive configuration and real-time information

4. llm-tldr 📊

Source: https://github.com/parcadei/llm-tldr Provides: 95% token reduction via 5-layer code analysis Key Feature: Semantic search and impact analysis

5. ui-ux-pro-max-skill 🎨

Source: https://github.com/nextlevelbuilder/ui-ux-pro-max-skill Provides: Professional UI/UX design agent with comprehensive patterns Key Feature: PROACTIVELY auto-triggering for all design work

6. @iannuttall/ralph 🤖

Source: https://github.com/iannuttall/ralph Provides: Autonomous agent looping with background execution Key Feature: "Fire and forget" multi-iteration development

7. claude-codex-settings 📋

Source: https://github.com/fcakyon/claude-codex-settings Provides: MCP configuration best practices (reference) Key Feature: Proven integration patterns


🎯 Real-Life Impact: Before vs After

Scenario Without Suite With Suite Impact
Debugging Errors Paste text manually, miss context Upload screenshot → Instant diagnosis 5x faster
Implementing UI Describe in words, iterate 10+ times Upload design → Exact code generated 10x faster
Understanding Code Read files manually, hit token limits TLDR 5-layer analysis, 95% token savings 20x faster
Writing Tests Write manually, forget often Auto-triggered after every code change Always tested
Code Search grep for exact names Semantic search by behavior Finds by intent
Web Research Outdated training data Real-time web search Always current
Refactoring Risk breaking changes Impact analysis, safe refactoring Zero breaking changes
Multi-Agent Tasks Manual orchestration Automatic coordination Hands-free delivery

🤝 Community & Contributing

This suite is 100% open source and available on GitHub.

  • Star the repo
  • 🐛 Report issues
  • 🔄 Submit pull requests
  • 💡 Contribute your own agents!

📝 License

MIT License - Feel free to use and modify for your needs.


Built for developers who ship. 🚀

Description
🚀 Ultimate Claude Code & GLM Suite - 40+ specialized AI agents, MCP tools, auto-triggering automation. Works with Anthropic Claude and Z.AI/GLM models.
https://www.rommark.dev
Readme 793 KiB
Languages
Shell 85.8%
Python 13%
Dockerfile 1.2%