# 🚀 Claude Code & GLM Suite - Master Integration Prompt > **Complete installation with ALL sources, explanations, and real-life examples** --- ## ⚠️ BEFORE YOU BEGIN - Read This First! ### **If Using Z.AI / GLM Coding Plan (90% cheaper):** **You MUST configure GLM FIRST before using Claude Code!** **🎯 EASIEST METHOD - Use Z.AI Coding Helper Wizard:** ```bash # Step 1: Install the coding helper npm install -g @z_ai/coding-helper # Step 2: Run the interactive GLM setup wizard npx @z_ai/coding-helper init # The wizard will: # - Ask for your Z.AI API key # - Configure Claude Code for GLM automatically # - Set up proper model mappings (glm-4.5-air, glm-4.7) # - Verify everything works # Step 3: Start Claude Code with GLM configured claude # Step 4: Verify GLM is working (enter /status when prompted) /status ``` **📖 Official GLM Documentation:** https://docs.z.ai/devpack/tool/claude --- **Alternative: Manual Configuration (if you prefer):** ```bash # Step 1: Get your API key # Visit: https://z.ai/ # Sign up for GLM Coding Plan and copy your API key # Step 2: Install Claude Code (if not installed) npm install -g @anthropic-ai/claude-code # Step 3: Create Claude Code settings 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 # Step 4: Start Claude Code claude ``` --- ### **If Using Anthropic Claude (Official API):** ```bash # Step 1: Get your API key # Visit: https://console.anthropic.com/ # Step 2: Create Claude Code settings 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 # Step 3: Install Claude Code (if not installed) npm install -g @anthropic-ai/claude-code # Step 4: Start Claude Code claude ``` --- ## 📋 HOW TO USE THE MASTER PROMPT **Once Claude Code is running and configured:** ### **✂️ COPY FROM HERE:** ```text ═══════════════════════════════════════════════════════════════════════════════ I want to install the Ultimate Claude Code & GLM Customization Suite with ALL integrations including agents, MCP tools, code analysis, and automation. Please perform the following complete integration: ## Overview: What We're Installing This suite includes 6 major components from open-source projects: 1. **contains-studio/agents** - 37 specialized AI agents with auto-triggering 2. **@z_ai/mcp-server** - 8 vision and analysis tools (screenshots, videos, diagrams) 3. **@z_ai/coding-helper** - Web search, GitHub integration, GLM setup wizard 4. **llm-tldr** - Token-efficient code analysis (95% reduction, semantic search) 5. **ui-ux-pro-max-skill** - Professional UI/UX design agent with PROACTIVELY auto-triggering 6. **claude-codex-settings** - MCP configuration patterns and best practices (reference) 7. **Ralph** - Autonomous agent coordination patterns (reference, integrated into contains-studio agents) Each component is explained below with real-life examples showing the benefits. --- ## Step 1: Install Contains Studio Agents (38 agents with PROACTIVELY auto-triggering) Source: https://github.com/contains-studio/agents Clone the contains-studio/agents repository: git clone https://github.com/contains-studio/agents.git /tmp/contains-studio-agents Copy all agents to Claude Code agents directory: cp -r /tmp/contains-studio-agents/agents/* ~/.claude/agents/ ### What This Provides: 37 specialized agents across 8 departments: - **Engineering (7):** AI Engineer, Backend Architect, DevOps Automator, Frontend Developer, Mobile Builder, Rapid Prototyper, Test Writer/Fixer - **Marketing (7):** TikTok Strategist, Growth Hacker, Content Creator, Instagram Curator, Reddit Builder, Twitter Engager, App Store Optimizer - **Design (6):** Brand Guardian, UI Designer, UX Researcher, Visual Storyteller, Whimsy Injector, **UI/UX Pro Max** - **Product (3):** Feedback Synthesizer, Sprint Prioritizer, Trend Researcher - **Project Management (3):** Experiment Tracker, Project Shipper, Studio Producer - **Studio Operations (5):** Analytics Reporter, Finance Tracker, Infrastructure Maintainer, Legal Compliance Checker, Support Responder - **Testing (5):** API Tester, Performance Benchmarker, Test Results Analyzer, Tool Evaluator, Workflow Optimizer - **Bonus (3):** Studio Coach, Agent Updater, Joker ### 🎯 Auto-Triggering System: How Agents Coordinate **Architecture Overview:** The 38 agents are divided into two types: - **7 PROACTIVELY Coordinators** - Auto-trigger based on context and coordinate specialists - **1 Utility Agent** - Manually triggered for maintenance (agent-updater) - **30 Specialist Agents** - Execute specific domain tasks when called **How It Works:** There are **two pathways** to use agents: 1. **Automatic** - Coordinators auto-trigger and call specialists as needed 2. **Direct** - You manually invoke any specialist for precise control This gives you automation when you want it, control when you need it. --- **7 PROACTIVELY Agents** (meta-coordinators that auto-trigger based on context): **Plus 1 Utility Agent** (manually triggered for maintenance): #### Design Department (2) 1. **ui-ux-pro-max** - Triggers on UI/UX design work - Professional design patterns and accessibility - 50+ styles, 97 color palettes, WCAG compliance - Example: "Create a pricing page" → ui-ux-pro-max applies professional design patterns 2. **whimsy-injector** - Triggers after UI/UX changes - Adds delightful micro-interactions - Makes interfaces memorable - Example: You create a loading spinner → whimsy-injector adds bounce animation and encouraging messages #### Engineering Department (1) 3. **test-writer-fixer** - Triggers after code modifications - Automatically writes comprehensive tests - Fixes broken tests - Example: You modify authentication code → test-writer-fixer writes unit tests automatically #### Project Management Department (3) 4. **experiment-tracker** - Triggers when experiments are started or modified - Tracks A/B tests and feature experiments - Defines metrics and monitors results - Example: You add a feature flag → experiment-tracker sets up tracking and success metrics 5. **studio-producer** - Triggers when coordinating across multiple teams - Cross-team coordination and resource allocation - Workflow optimization and dependency management - Example: "Design and engineering need to collaborate" → studio-producer schedules and coordinates 6. **project-shipper** - Triggers when approaching launch milestones - Launch coordination and release management - Go-to-market strategy and stakeholder communication - Example: "We're releasing next week" → project-shipper plans launch activities #### Bonus Department (1) 7. **studio-coach** - Triggers on complex multi-agent tasks - Coordinates multiple specialists - Motivates and aligns agents when stuck - Example: "Build a viral TikTok app in 2 weeks" → studio-coach organizes frontend, backend, marketing agents #### Utility Agent (On-Demand) 8. **agent-updater** - Manually triggered for agent synchronization - Checks GitHub for agent updates - Downloads and installs new/updated agents safely - Preserves local customizations - Example: "Check for agent updates" → agent-updater fetches latest from GitHub and syncs your installation --- **🔄 Real Workflow Example:** You: "I need a viral TikTok app in 2 weeks" ↓ [studio-coach PROACTIVELY triggers] ↓ studio-coach analyzes and coordinates: → rapid-prototyper (specialist) builds MVP → tiktok-strategist (specialist) plans viral features → frontend-developer (specialist) builds UI ↓ [whimsy-injector PROACTIVELY triggers] ↓ whimsy-injector adds delightful touches ↓ [project-shipper PROACTIVELY triggers] ↓ project-shipper plans launch strategy ↓ Result: Complete app, launch-ready ✓ **Key Point:** You don't need to manually orchestrate! The 7 coordinators automatically: - Detect context (design work, code changes, launches, etc.) - Call appropriate specialist agents - Coordinate multi-agent workflows - Ensure quality and completeness You can ALSO directly call any specialist agent anytime for manual control. --- ## Step 1.5: Install UI/UX Pro Max Agent (PROACTIVELY Auto-Triggers) Source: https://github.com/nextlevelbuilder/ui-ux-pro-max-skill Clone the ui-ux-pro-max-skill repository: git clone https://github.com/nextlevelbuilder/ui-ux-pro-max-skill.git /tmp/ui-ux-pro-max-skill Install UI/UX Pro Max agent with PROACTIVELY triggers: mkdir -p ~/.claude/agents/design wget -O ~/.claude/agents/design/ui-ux-pro-max.md https://raw.githubusercontent.com/github.rommark.dev/admin/claude-code-glm-suite/main/agents/design/ui-ux-pro-max.md Also install the SKILL file for enhanced compatibility: mkdir -p ~/.claude/skills/ui-ux-pro-max cp /tmp/ui-ux-pro-max-skill/.claude/skills/ui-ux-pro-max/SKILL.md ~/.claude/skills/ui-ux-pro-max/ ### What This Provides: **ui-ux-pro-max agent** with PROACTIVELY auto-triggering for: - UI component creation (buttons, modals, forms, cards, navbars) - Page design (landing pages, dashboards, pricing pages) - UI/UX review and audits - Style guide application (colors, typography, spacing) - Accessibility compliance (WCAG 2.1 AA/AAA) - Tech-stack specific patterns (React, Next.js, Vue, Tailwind, shadcn/ui) **Comprehensive design knowledge:** - 50+ design styles (glassmorphism, minimalism, brutalism, etc.) - 97 color palettes by industry - 57 font pairings with Google Fonts imports - Accessibility standards (contrast ratios, keyboard nav, ARIA labels) - Professional design patterns (no emoji icons, proper hover states) **Key Features:** - Automatic UI/UX review during design work - Professional design patterns applied proactively - Accessibility-first approach (WCAG 2.1 AA/AAA) - Comprehensive styling guidelines --- ## Step 1.75: Install Agent Sync Script (Keep Agents Updated) Source: https://github.rommark.dev/admin/claude-code-glm-suite Install the automated sync script to keep your agents up-to-date: # Download sync-agents.sh wget -O ~/.claude/sync-agents.sh https://raw.githubusercontent.com/github.rommark.dev/admin/claude-code-glm-suite/main/sync-agents.sh # Make it executable chmod +x ~/.claude/sync-agents.sh ### What This Provides: **Automated agent synchronization:** - Fetches latest agents from official GitHub repository - Creates timestamped backups before updating - Detects new, updated, and customized agents - Safely updates while preserving your customizations - Commits changes to git (if configured) - Pushes updates to your Gitea repository **Usage:** # Run sync manually ~/.claude/sync-agents.sh # Or set Gitea repository URL to auto-push export GITEA_REPO_URL="https://github.rommark.dev/admin/claude-code-glm-suite.git" ~/.claude/sync-agents.sh # Also update repository agents (for installers) export REPO_AGENTS_DIR="/path/to/claude-code-glm-suite/agents" ~/.claude/sync-agents.sh **How it works:** 1. Clones latest agents from `https://github.com/contains-studio/agents` 2. Compares with your local `~/.claude/agents/` 3. Identifies: - ✨ New agents to add - 📝 Updated agents to refresh - ⚠️ Custom agents to preserve 4. Creates backup: `~/.claude/agents.backup.YYYYMMDD-HHMMSS/` 5. Applies updates safely 6. Reports all changes 7. [Optional] Commits to git and pushes to Gitea **Key Features:** - **Safe Updates**: Always creates backups before modifying - **Smart Detection**: Preserves agents you've customized - **Dual Sync**: Updates both local agents AND repository agents - **Git Integration**: Commits and pushes automatically - **Detailed Logging**: Tracks all changes in `~/.claude/agents/update.log` **Keeping Agents Updated:** Run the sync script regularly (weekly or monthly) to get the latest agent improvements: # Add to crontab for automatic weekly sync 0 2 * * 0 ~/.claude/sync-agents.sh Or manually check for updates anytime: ~/.claude/sync-agents.sh **Rollback if needed:** # List backups ls -la ~/.claude/agents.backup.* # Restore a backup rm -rf ~/.claude/agents mv ~/.claude/agents.backup.YYYYMMDD-HHMMSS ~/.claude/agents --- ## Step 2: Install MCP Vision & Analysis Tools Source: https://github.com/zai-ai/mcp-server Install Z.AI MCP server for vision tools: npm install -g @z_ai/mcp-server Verify installation: npx @z_ai/mcp-server --help ### What This Provides (8 MCP Tools): 1. **analyze_image** - Understand any image (screenshots, photos, designs) 2. **analyze_video** - Analyze video content for key moments 3. **ui_to_artifact** - Convert UI screenshots to code 4. **extract_text** - OCR text extraction from images 5. **diagnose_error** - Understand errors from screenshots 6. **ui_diff_check** - Compare two UI screenshots 7. **analyze_data_viz** - Extract insights from dashboards/charts 8. **understand_diagram** - Understand technical diagrams (UML, flowcharts) **Key Features:** - Screenshot-to-code conversion - Error diagnosis from images - Video and diagram understanding - UI comparison and analysis --- ## Step 3: Install MCP Web & GitHub Tools Source: https://github.com/fcakyon/claude-codex-settings (inspired by) Install Z.AI coding helper: npm install -g @z_ai/coding-helper Verify installation: npx @z_ai/coding-helper --help ### What This Provides (3 MCP Tools): 1. **web-search-prime** - AI-optimized web search for current information 2. **web-reader** - Convert any web page to clean markdown 3. **zread** - Read and analyze entire GitHub repositories **Key Features:** - Real-time web search for current information - Repository analysis without manual file pasting - Web page to clean markdown conversion --- ## Step 4: Install llm-tldr (Token-Efficient Code Analysis) Source: https://github.com/parcadei/llm-tldr Install llm-tldr: pip install llm-tldr Initialize for current directory: tldr warm . ### What This Provides: **95% token reduction** while preserving code understanding via 5-layer analysis: - **Layer 1 (AST)** - Functions, classes, imports structure - **Layer 2 (Call Graph)** - Who calls what (forward/backward) - **Layer 3 (CFG)** - Control flow, complexity metrics - **Layer 4 (DFG)** - Data flow, variable transformations - **Layer 5 (PDG)** - Program dependence, slicing for debugging **18 MCP Tools including:** - `context` - LLM-ready summaries (95% token savings) - `semantic` - Search by behavior, not just text - `slice` - Show only code affecting a specific line - `impact` - Who calls this function? (refactoring safety) - `cfg` - Control flow graph - `dfg` - Data flow graph - And 12 more... **Key Features:** - 95% token reduction for large codebases - Semantic search by behavior (not just text) - Program slicing for precise debugging - Impact analysis for safe refactoring --- ## Step 5: Configure MCP Servers in Claude Code Create MCP configuration for TLDR: mkdir -p ~/.claude cat > ~/.claude/claude_desktop_config.json << 'EOF' { "mcpServers": { "tldr": { "command": "tldr-mcp", "args": ["--project", "."] }, "zai-vision": { "command": "npx", "args": ["@z_ai/mcp-server"] } } } EOF Note: TLDR MCP server provides 18 tools for code analysis. Vision tools from @z_ai/mcp-server are automatically available. --- ## Step 6: Configure Hooks-Based Auto-Triggering (Optional) Create hooks.json for additional auto-triggering: cat > ~/.claude/hooks.json << 'EOF' { "userPromptSubmitHook": "test-writer-fixer@agent", "toolOutputHook": "whimsy-injector@agent" } EOF Note: PROACTIVELY agents (studio-coach, experiment-tracker) work automatically without hooks. --- ## Step 7: Verify Complete Installation Run comprehensive checks: # 1. Verify agents (should be 38+ files) ls -la ~/.claude/agents/ find ~/.claude/agents -name "*.md" | wc -l # 2. Verify MCP tools npx @z_ai/mcp-server --help npx @z_ai/coding-helper --help tldr --help # 3. Verify TLDR indexing tldr status . # 4. Test Claude Code claude --version Expected results: - ✅ 39+ agent files (38 agents + README) - ✅ All 8 departments present - ✅ MCP tools accessible - ✅ TLDR indexed current directory - ✅ Settings configured --- ## Summary: What You Now Have ### 40+ AI Agents Organized across 8 departments with PROACTIVELY auto-triggering ### 15+ MCP Tools - 8 vision/analysis tools (@z_ai/mcp-server) - 3 web/GitHub tools (@z_ai/coding-helper) - 18 code analysis tools (llm-tldr) ### Two Auto-Triggering Systems - PROACTIVELY keyword (context-aware) - Hooks-based (event-driven) ### Complete Integration Benefits **Token Efficiency:** - TLDR reduces code context by 95% - $100/month savings on API costs for large codebases **Code Understanding:** - 5-layer analysis (AST → PDG) - Semantic search by behavior - Impact analysis for safe refactoring **Visual Capabilities:** - Screenshot-to-code conversion - Error diagnosis from images - Video and diagram understanding **Automation:** - Auto-test writing after code changes - Auto-UI enhancement after design changes - Auto-coordination for complex tasks **Up-to-Date Information:** - Real-time web search - Repository analysis - Current documentation Please execute this complete integration step by step and confirm when each component is installed. ═══════════════════════════════════════════════════════════════════════════════ ``` **✂️ COPY ENDS HERE** --- --- # ═══════════════════════════════════════════════════════════════════════════════ # 📖 REAL-LIFE EXAMPLES: HOW AUTO-TRIGGERING WORKS # ═══════════════════════════════════════════════════════════════════════════════ > ⚠️ **IMPORTANT: These are ILLUSTRATIVE EXAMPLES ONLY** > > The examples below demonstrate the conceptual difference between working **without** auto-triggering agents versus **with** auto-triggering agents. > These are simplified scenarios to help you understand how the PROACTIVELY system improves your workflow. > > **These are not actual output promises** - actual results will vary based on your specific use case, context, and model capabilities. ## Example 1: Adding OAuth Authentication ### ❌ WITHOUT Auto-Triggering Agents You: Help me add OAuth to my app Claude: [Writes code, but no tests] You: [Manually write tests later] Claude: [Fixes bugs] ### ✅ WITH Auto-Triggering Agents You: Help me add OAuth to my app Claude: [Writes code] [test-writer-fixer PROACTIVELY triggers] test-writer-fixer: I've automatically created comprehensive tests for your OAuth implementation Result: Code + tests complete in one interaction ✓ --- ## Example 2: Creating a Loading Spinner ### ❌ WITHOUT Auto-Triggering Agents You: Create a loading spinner Claude: [Creates basic spinner] You: [Manually request improvements later] Claude: [Adds animation] ### ✅ WITH Auto-Triggering Agents You: Create a loading spinner Claude: [Creates spinner] [whimsy-injector PROACTIVELY triggers] whimsy-injector: I've enhanced your spinner with bounce animation and encouraging messages Result: Delightful spinner created automatically ✓ --- ## Example 3: Launching a New Feature ### ❌ WITHOUT Auto-Triggering Agents You: We're launching next week Claude: [Doesn't know what to prepare] You: [Manually create launch checklist] Claude: [Helps with specific items] ### ✅ WITH Auto-Triggering Agents You: We're launching next week [project-shipper PROACTIVELY triggers] project-shipper: I've created a complete launch plan with: - Pre-launch readiness checklist - Go-to-market strategy - Stakeholder communication plan - Success metrics and monitoring Result: Launch-ready plan created automatically ✓ --- ## Example 4: Adding a Feature Flag ### ❌ WITHOUT Auto-Triggering Agents You: Add feature flag for new checkout Claude: [Adds flag, but no tracking] You: [Manually set up analytics later] ### ✅ WITH Auto-Triggering Agents You: Add feature flag for new checkout Claude: [Adds flag] [experiment-tracker PROACTIVELY triggers] experiment-tracker: I've configured tracking for this experiment: - Success metrics defined - Analytics events set up - Rollout plan created - Sample size calculated Result: A/B test ready to run ✓ --- ## Example 5: Complex Multi-Agent Task ### ❌ WITHOUT Auto-Triggering Agents You: Build viral TikTok app in 2 weeks Claude: [Overwhelmed, doesn't know where to start] You: [Manually coordinate frontend, backend, marketing teams] ### ✅ WITH Auto-Triggering Agents You: Build viral TikTok app in 2 weeks [studio-coach PROACTIVELY triggers] studio-coach: I'll coordinate this complex project: → Calling rapid-prototyper for MVP → Calling tiktok-strategist for viral features → Calling frontend-developer for UI → Calling project-hipper for launch planning [All agents work together seamlessly] Result: Complete app, launch-ready, on time ✓ --- ## Key Differences Summary | Aspect | Without Auto-Trigger | With Auto-Trigger | |--------|---------------------|-------------------| | **Test Coverage** | Manual, forgettable | Automatic, comprehensive | | **UI Polish** | Basic, functional | Delightful, memorable | | **Launch Prep** | Last-minute, chaotic | Planned, organized | | **Experiment Tracking** | Missing, incomplete | Defined, measurable | | **Complex Projects** | Overwhelming, fragmented | Coordinated, smooth | | **Follow-up Required** | Always needed | Built-in | --- ## Why This Matters **Time Savings:** - Without: Multiple back-and-forth interactions - With: Complete in one interaction **Quality:** - Without: Inconsistent, forgets steps - With: Comprehensive, best practices applied **Peace of Mind:** - Without: Did I remember everything? - With: Agents handle it automatically **Scalability:** - Without: Manual coordination doesn't scale - With: Automated coordination handles complexity --- ## ⚡ PROACTIVELY vs Hooks-Based ### PROACTIVELY System (Context-Aware) **How it works:** - Claude analyzes the context of your request - Automatically determines which coordinator to trigger - Coordinator calls specialist agents as needed **Examples:** - You write code → test-writer-fixer triggers - You design UI → whimsy-injector triggers - You mention launch → project-shipper triggers **Benefits:** - No configuration needed - Works based on natural language context - Can be overridden by manual requests ### Hooks-Based System (Event-Driven) **How it works:** - Configured in `~/.claude/hooks.json` - Triggers on specific events (prompt submit, tool output, etc.) **Example Configuration:** ```json { "userPromptSubmitHook": "test-writer-fixer@agent", "toolOutputHook": "whimsy-injector@agent" } ``` **Benefits:** - Predictable triggers - Fine-grained control - Works alongside PROACTIVELY system ### Combined Power You can use BOTH systems together: - PROACTIVELY: Automatic context-aware triggers - Hooks: Additional event-driven triggers - Result: Comprehensive automation coverage --- # 📚 AGENT DEPARTMENTS AND SPECIALTIES ## Engineering Department (7 agents) 1. **ai-engineer** - ML/LLM feature integration 2. **backend-architect** - API design, database optimization 3. **devops-automator** - CI/CD, cloud infrastructure 4. **frontend-developer** - React/Vue/Angular UI development 5. **mobile-app-builder** - iOS/Android native apps 6. **rapid-prototyper** - Quick MVPs and prototypes 7. **test-writer-fixer** - Auto test writing (PROACTIVELY) ## Marketing Department (7 agents) 1. **tiktok-strategist** - Viral TikTok marketing 2. **growth-hacker** - Viral growth loops 3. **content-creator** - Multi-platform content 4. **instagram-curator** - Visual content strategy 5. **reddit-community-builder** - Reddit engagement 6. **twitter-engager** - Twitter growth 7. **app-store-optimizer** - ASO and rankings ## Design Department (6 agents) 1. **brand-guardian** - Brand consistency 2. **ui-designer** - Interface design 3. **ux-researcher** - User research 4. **visual-storyteller** - Visual narratives 5. **whimsy-injector** - Delight injection (PROACTIVELY) 6. **ui-ux-pro-max** - Professional UI/UX (PROACTIVELY) ## Product Department (3 agents) 1. **feedback-synthesizer** - User feedback analysis 2. **sprint-prioritizer** - Feature prioritization 3. **trend-researcher** - Market trend identification ## Project Management Department (3 agents) 1. **experiment-tracker** - A/B test tracking (PROACTIVELY) 2. **project-shipper** - Launch coordination (PROACTIVELY) 3. **studio-producer** - Team coordination (PROACTIVELY) ## Studio Operations Department (5 agents) 1. **analytics-reporter** - Data insights 2. **finance-tracker** - Financial management 3. **infrastructure-maintainer** - System maintenance 4. **legal-compliance-checker** - Legal compliance 5. **support-responder** - Customer support ## Testing Department (5 agents) 1. **api-tester** - API testing 2. **performance-benchmarker** - Performance optimization 3. **test-results-analyzer** - Test analysis 4. **tool-evaluator** - Tool assessment 5. **workflow-optimizer** - Process improvement ## Bonus Department (3 agents) 1. **studio-coach** - Agent coordination (PROACTIVELY) 2. **agent-updater** - Agent updates (on-demand) 3. **joker** - Humor injection --- # 🔧 CONFIGURATION FILES ## ~/.claude/settings.json Main Claude Code configuration file: ```json { "env": { "ANTHROPIC_AUTH_TOKEN": "your-api-key", "ANTHROPIC_BASE_URL": "https://api.anthropic.com", "API_TIMEOUT_MS": "3000000" } } ``` ### For Z.AI / GLM: ```json { "env": { "ANTHROPIC_AUTH_TOKEN": "your-zai-key", "ANTHROPIC_BASE_URL": "https://api.z.ai/api/anthropic", "ANTHROPIC_DEFAULT_HAIKU_MODEL": "glm-4.5-air", "ANTHROPIC_DEFAULT_SONNET_MODEL": "glm-4.7", "ANTHROPIC_DEFAULT_OPUS_MODEL": "glm-4.7" } } ``` ## ~/.claude/claude_desktop_config.json MCP server configuration: ```json { "mcpServers": { "tldr": { "command": "tldr-mcp", "args": ["--project", "."] }, "zai-vision": { "command": "npx", "args": ["@z_ai/mcp-server"] }, "zai-web": { "command": "npx", "args": ["@z_ai/coding-helper"] } } } ``` ## ~/.claude/hooks.json Auto-triggering hooks: ```json { "userPromptSubmitHook": "test-writer-fixer@agent", "toolOutputHook": "whimsy-injector@agent" } ``` --- # 🎯 QUICK REFERENCE ## Available Commands ### Sync Agents ```bash ~/.claude/sync-agents.sh ``` ### Verify Installation ```bash ./verify-claude-setup.sh ``` ### Check TLDR Status ```bash tldr status . ``` ### Test Claude Code ```bash claude --version ``` ## Environment Variables ```bash # Auto-push to Gitea after sync export GITEA_REPO_URL="https://github.rommark.dev/admin/claude-code-glm-suite.git" # Update repository agents during sync export REPO_AGENTS_DIR="/path/to/repo/agents" ``` ## Troubleshooting ### Agents not triggering? - Check `~/.claude/agents/` directory - Verify agent files exist and have content - Restart Claude Code ### MCP tools not available? - Check `~/.claude/claude_desktop_config.json` - Verify MCP servers are installed - Restart Claude Code ### TLDR not working? - Run `tldr warm .` in project directory - Check Python installation - Verify `tldr-mcp` is in PATH --- # 📖 ADDITIONAL RESOURCES ## Official Documentation - **Claude Code**: https://docs.anthropic.com/en/docs/claude-code - **Z.AI / GLM**: https://docs.z.ai/devpack/tool/claude - **contains-studio/agents**: https://github.com/contains-studio/agents - **@z_ai/mcp-server**: https://github.com/zai-ai/mcp-server - **llm-tldr**: https://github.com/parcadei/llm-tldr ## Community & Support - **Claude Code Sub-Agents**: https://docs.anthropic.com/en/docs/claude-code/sub-agents - **Gitea Repository**: https://github.rommark.dev/admin/claude-code-glm-suite ## Changelog & Updates - Check the repository regularly for updates - Use `~/.claude/sync-agents.sh` to keep agents current - Review MASTER-PROMPT.md for latest features --- **Last Updated**: 2025-01-16 **Version**: 2.0 **Maintained By**: rommark.dev