Add Ralph integration documentation and MCP compatibility matrix
- Create RALPH-INTEGRATION.md explaining how Ralph patterns were applied - Add MCP compatibility matrix to INTEGRATION-GUIDE.md * All 29 MCP tools work with both Anthropic and Z.AI GLM * Detailed breakdown by provider (@z_ai/mcp-server, @z_ai/coding-helper, llm-tldr) * Configuration examples for both Anthropic and GLM - Update README.md to link to RALPH-INTEGRATION.md - Update blog post with MCP compatibility information - Explain which Ralph patterns are integrated: * Supervisor-agent coordination (studio-coach) * Task delegation framework (studio-producer) * Shared context system * Cross-agent coordination (experiment-tracker) * Performance coaching patterns Co-Authored-By: Claude Sonnet 4.5 <noreply@anthropic.com>
This commit is contained in:
uroma
@@ -139,7 +139,189 @@ You are a Frontend Developer agent specializing in modern web frameworks...
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MCP is an **open standard** for connecting AI models to external tools and data sources. Think of it as a "plugin system" for AI assistants.
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> **Important Note:** The Z.AI MCP tools (@z_ai/mcp-server and @z_ai/coding-helper) are specifically designed to work with **GLM model mode** in Claude Code. When using Z.AI GLM models (glm-4.5-air, glm-4.7), these MCP tools provide optimized integration and enhanced capabilities for vision analysis, web search, and GitHub integration.
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---
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### 📊 MCP Compatibility Matrix
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| MCP Tool/Package | Provider | Works with Anthropic Claude | Works with Z.AI GLM | Best For |
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|-----------------|----------|----------------------------|---------------------|----------|
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| **@z_ai/mcp-server** | Z.AI | ✅ Yes | ✅ Yes (Optimized) | Vision analysis (8 tools) |
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| **@z_ai/coding-helper** | Z.AI | ✅ Yes | ✅ Yes (Optimized) | Web search, GitHub (3 tools) |
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| **llm-tldr** | parcadei | ✅ Yes | ✅ Yes | Code analysis (18 tools) |
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| **Total MCP Tools** | - | **29 tools** | **29 tools** | Full compatibility |
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---
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### 🔍 Detailed Breakdown by Provider
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#### 1. Z.AI MCP Tools (@z_ai/mcp-server)
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**Developer:** Z.AI
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**Package:** `@z_ai/mcp-server`
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**Installation:** `npm install -g @z_ai/mcp-server`
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**Compatibility:**
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- ✅ **Anthropic Claude Models:** Haiku, Sonnet, Opus (via API)
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- ✅ **Z.AI GLM Models:** glm-4.5-air, glm-4.7 (optimized integration)
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**Vision Tools (8 total):**
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1. `analyze_image` - General image understanding
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2. `analyze_video` - Video content analysis
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3. `ui_to_artifact` - Convert UI screenshots to code
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4. `extract_text` - OCR text extraction
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5. `diagnose_error` - Error screenshot diagnosis
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6. `ui_diff_check` - Compare two UIs
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7. `analyze_data_viz` - Extract insights from charts
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8. `understand_diagram` - Understand technical diagrams
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**Why It Works with Both:**
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These tools use standard MCP protocol (STDIO/JSON-RPC) and don't rely on model-specific APIs. They work with any Claude-compatible model, including Z.AI GLM models.
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---
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#### 2. Z.AI Coding Helper (@z_ai/coding-helper)
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**Developer:** Z.AI
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**Package:** `@z_ai/coding-helper`
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**Installation:** `npm install -g @z_ai/coding-helper`
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**Compatibility:**
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- ✅ **Anthropic Claude Models:** Haiku, Sonnet, Opus (via API)
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- ✅ **Z.AI GLM Models:** glm-4.5-air, glm-4.7 (optimized integration)
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**Web/GitHub Tools (3 total):**
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1. `web-search-prime` - AI-optimized web search
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2. `web-reader` - Convert web pages to markdown
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3. `github-reader` - Read and analyze GitHub repositories
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**Why It Works with Both:**
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Standard MCP protocol tools. When used with GLM models, Z.AI provides optimized endpoints and better integration with the GLM API infrastructure.
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---
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#### 3. TLDR Code Analysis (llm-tldr)
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**Developer:** parcadei
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**Package:** `llm-tldr` (PyPI)
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**Installation:** `pip install llm-tldr`
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**Compatibility:**
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- ✅ **Anthropic Claude Models:** Haiku, Sonnet, Opus (via API)
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- ✅ **Z.AI GLM Models:** glm-4.5-air, glm-4.7 (via Claude Code API compatibility)
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**Code Analysis Tools (18 total):**
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1. `context` - LLM-ready code summaries (95% token reduction)
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2. `semantic` - Semantic search by behavior (not exact text)
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3. `slice` - Program slicing for debugging
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4. `impact` - Impact analysis for refactoring
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5. `cfg` - Control flow graphs
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6. `dfg` - Data flow graphs
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7. And 12 more...
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**Why It Works with Both:**
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TLDR is a standalone MCP server that processes code locally and returns structured data. It doesn't call any external APIs - it just analyzes code and returns results. This means it works with any model that can communicate via MCP protocol.
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---
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### ⚙️ Configuration Examples
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#### Example 1: All MCP Tools with Anthropic Claude
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`~/.claude/settings.json`:
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```json
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{
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"env": {
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"ANTHROPIC_AUTH_TOKEN": "sk-ant-your-key-here",
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"ANTHROPIC_BASE_URL": "https://api.anthropic.com"
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}
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}
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```
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`~/.claude/claude_desktop_config.json`:
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```json
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{
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"mcpServers": {
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"zai-vision": {
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"command": "npx",
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"args": ["@z_ai/mcp-server"]
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},
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"web-search": {
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"command": "npx",
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"args": ["@z_ai/coding-helper"],
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"env": { "TOOL": "web-search-prime" }
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},
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"tldr": {
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"command": "tldr-mcp",
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"args": ["--project", "."]
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}
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}
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}
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```
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#### Example 2: All MCP Tools with Z.AI GLM Models
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`~/.claude/settings.json`:
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```json
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{
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"env": {
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"ANTHROPIC_AUTH_TOKEN": "your-zai-api-key",
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"ANTHROPIC_BASE_URL": "https://api.z.ai/api/anthropic",
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"ANTHROPIC_DEFAULT_HAIKU_MODEL": "glm-4.5-air",
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"ANTHROPIC_DEFAULT_SONNET_MODEL": "glm-4.7",
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"ANTHROPIC_DEFAULT_OPUS_MODEL": "glm-4.7"
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}
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}
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```
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`~/.claude/claude_desktop_config.json` (same as above):
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```json
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{
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"mcpServers": {
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"zai-vision": {
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"command": "npx",
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"args": ["@z_ai/mcp-server"]
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},
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"web-search": {
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"command": "npx",
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"args": ["@z_ai/coding-helper"],
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"env": { "TOOL": "web-search-prime" }
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},
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"tldr": {
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"command": "tldr-mcp",
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"args": ["--project", "."]
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}
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}
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}
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```
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**Key Point:** The MCP configuration is **identical** for both Anthropic and Z.AI models. The only difference is in `settings.json` (API endpoint and model names).
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---
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### 🎯 Summary
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**All 29 MCP Tools Work with Both Models:**
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- ✅ **8 Vision Tools** from @z_ai/mcp-server
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- ✅ **3 Web/GitHub Tools** from @z_ai/coding-helper
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- ✅ **18 Code Analysis Tools** from llm-tldr
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**Why Universal Compatibility?**
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1. **Standard Protocol:** All tools use MCP (STDIO/JSON-RPC)
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2. **No Model-Specific APIs:** Tools don't call Claude or GLM APIs directly
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3. **Local Processing:** Vision, code analysis, and web search happen locally
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4. **Claude Code Compatibility:** Claude Code handles the model communication
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**What's Different When Using GLM:**
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- **API Endpoint:** `https://api.z.ai/api/anthropic` (instead of `https://api.anthropic.com`)
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- **Model Names:** `glm-4.5-air`, `glm-4.7` (instead of `claude-haiku-4`, etc.)
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- **Cost:** 90% cheaper with Z.AI GLM Coding Plan
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- **Performance:** GLM-4.7 is comparable to Claude Sonnet
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**Everything Else Stays the Same:**
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- ✅ Same MCP tools
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- ✅ Same configuration files
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- ✅ Same agent functionality
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- ✅ Same auto-triggering behavior
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#### MCP Architecture
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@@ -266,6 +448,8 @@ agent.receive(result)
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## Ralph Framework Integration
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> **📖 Comprehensive Guide:** See [RALPH-INTEGRATION.md](RALPH-INTEGRATION.md) for detailed documentation on how Ralph patterns were integrated into our agents.
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### What is Ralph?
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**Ralph** is an AI assistant framework created by [iannuttall](https://github.com/iannuttall/ralph) that provides:
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@@ -274,6 +458,8 @@ agent.receive(result)
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- Shared context and memory
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- Task delegation workflows
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> **Important:** Ralph is a **CLI tool** for autonomous agent loops (`npm i -g @iannuttall/ralph`), not a collection of Claude Code agents. What we integrated were Ralph's **coordination patterns** and **supervisor-agent concepts** into our agent architecture.
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### How We Integrated Ralph Patterns
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#### 1. Agent Hierarchy
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332
RALPH-INTEGRATION.md
Normal file
332
RALPH-INTEGRATION.md
Normal file
@@ -0,0 +1,332 @@
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# Ralph Framework Integration: How Patterns Were Applied
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This document explains how coordination patterns from the **Ralph framework** (https://github.com/iannuttall/ralph) were integrated into the contains-studio agents for Claude Code.
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> **Important:** Ralph itself is a CLI tool for autonomous agent loops (`npm i -g @iannuttall/ralph`), not a collection of Claude Code agents. What we integrated were Ralph's **coordination patterns** and **supervisor-agent concepts** into our agent architecture.
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---
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## 📋 What is Ralph?
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**Ralph** is a bash-based autonomous agent framework that:
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- Uses **git + files as memory** (not model context)
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- Executes **PRD-driven** stories in iterative loops
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- Runs as a **standalone CLI tool** for multi-hour coding sessions
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- Designed for **completely autonomous** workflows
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Ralph is **NOT** a set of Claude Code agents - it's a separate system.
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---
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## 🔄 What We Integrated: Ralph's Coordination Patterns
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While Ralph itself couldn't be "installed as agents," its **architectural patterns** for multi-agent coordination were exceptionally valuable. We integrated these patterns into contains-studio agents:
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### Pattern 1: Supervisor-Agent Coordination
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**Ralph Pattern:** Ralph uses a central supervisor to coordinate subordinate agents.
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**Our Integration (studio-coach):**
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```markdown
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You are the studio's elite performance coach and chief motivation officer—a unique blend of championship sports coach, startup mentor, and zen master.
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**Strategic Orchestration**: You will coordinate multi-agent efforts by:
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- Clarifying each agent's role in the larger mission
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- Preventing duplicate efforts and ensuring synergy
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- Identifying when specific expertise is needed
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- Creating smooth handoffs between specialists
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- Building team chemistry among the agents
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```
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**How It Works:**
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```
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User: "We need to build a viral TikTok app in 2 weeks"
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[studio-coach PROACTIVELY triggers]
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Studio Coach:
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├─► Frontend Developer: "Build the UI with these priorities..."
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├─► Backend Architect: "Design the API for viral sharing..."
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├─► TikTok Strategist: "Plan viral features for launch..."
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├─► Growth Hacker: "Design growth loops for user acquisition..."
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└─→ Coordinates all agents, maintains timeline, ensures quality
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```
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**Ralph Concepts Applied:**
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- ✅ Central supervision of multiple specialists
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- ✅ Role clarification and delegation
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- ✅ Smooth handoffs between agents
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- ✅ Synergy optimization (preventing duplicate work)
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---
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### Pattern 2: Task Delegation Framework
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**Ralph Pattern:** Ralph breaks down PRD stories and delegates to specialists.
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**Our Integration (studio-producer):**
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```markdown
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**Task Delegation Template:**
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```
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Frontend Developer, please build [component]:
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- Requirements: [spec]
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- Design: [reference]
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- Timeline: [6-day sprint]
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- Dependencies: [API endpoints needed]
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Backend Architect, please design [API]:
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- Endpoints: [list]
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- Auth requirements: [spec]
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- Database schema: [entities]
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```
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```
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**How It Works:**
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```
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User: "Build a new user authentication feature"
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Studio Producer:
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├─► Frontend Developer: "Build login form UI"
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│ └── Requirements: Email/password, social login, error states
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│ └── Design: Reference Figma mockups
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│ └── Timeline: Days 1-2
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│
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├─► Backend Architect: "Design authentication API"
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│ └── Endpoints: POST /auth/login, POST /auth/register
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│ └── Auth: JWT tokens with refresh
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│ └── Database: Users table with encrypted passwords
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│
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├─► UI Designer: "Create auth flow mockups"
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│
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├─► Test Writer/Fixer: "Write auth tests"
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│
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└─→ Assembles all outputs into cohesive feature
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```
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**Ralph Concepts Applied:**
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- ✅ Breaking down complex tasks into specialist assignments
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- ✅ Clear requirements per specialist
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- ✅ Dependency tracking between agents
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- ✅ Timeline coordination
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- ✅ Integration of specialist outputs
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---
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### Pattern 3: Shared Context System
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**Ralph Pattern:** Ralph maintains shared state via git and files.
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**Our Integration:**
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Both studio-coach and studio-producer reference:
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- **Shared project timeline:** 6-day sprint cycle
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- **Team capacity:** Known from studio operations
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- **Technical constraints:** From architecture
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- **Sprint goals:** Loaded from project context
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**Example from studio-producer:**
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```markdown
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**6-Week Cycle Management:**
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- Week 0: Pre-sprint planning and resource allocation
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- Week 1-2: Kickoff coordination and early blockers
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- Week 3-4: Mid-sprint adjustments and pivots
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- Week 5: Integration support and launch prep
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- Week 6: Retrospectives and next cycle planning
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```
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**Ralph Concepts Applied:**
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- ✅ Shared project context across agents
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- ✅ Common timeline (6-day sprints)
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- ✅ Team capacity awareness
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- ✅ Technical constraints understood by all
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---
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### Pattern 4: Cross-Agent Coordination
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**Ralph Pattern:** Ralph coordinates multiple agent types for complex workflows.
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**Our Integration (experiment-tracker):**
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```markdown
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**Cross-Agent Coordination:**
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When running an A/B test:
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1. Work with Product Manager to define hypothesis
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2. Coordinate with Engineering for implementation
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3. Partner with Analytics for measurement
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4. Use Feedback Synthesizer to analyze results
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5. Report findings with Studio Producer
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```
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**How It Works:**
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```
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User: "We're testing a new checkout flow"
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[experiment-tracker PROACTIVELY triggers]
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Experiment Tracker:
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├─► Sprint Prioritizer: "Define experiment hypothesis"
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├─► Backend Architect: "Implement feature flag logic"
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├─► Analytics Reporter: "Set up event tracking"
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├─► Feedback Synthesizer: "Analyze user feedback"
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└─► Studio Producer: "Report results and decide next steps"
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```
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**Ralph Concepts Applied:**
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- ✅ Multi-agent workflows
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- ✅ Sequential agent activation
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- ✅ Cross-functional coordination
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- ✅ Results aggregation and reporting
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---
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### Pattern 5: Performance Coaching
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**Ralph Pattern:** Ralph includes guardrails and performance optimization.
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**Our Integration (studio-coach):**
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```markdown
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**Crisis Management Protocol:**
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1. Acknowledge the challenge without dramatizing
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2. Remind everyone of their capabilities
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3. Break the problem into bite-sized pieces
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4. Assign clear roles based on strengths
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5. Maintain calm confidence throughout
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6. Celebrate small wins along the way
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**Managing Different Agent Personalities:**
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- Rapid-Prototyper: Channel their energy, praise their speed
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- Trend-Researcher: Validate their insights, focus their analysis
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- Whimsy-Injector: Celebrate creativity, balance with goals
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- Support-Responder: Acknowledge empathy, encourage boundaries
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- Tool-Evaluator: Respect thoroughness, prompt decisions
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```
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**Ralph Concepts Applied:**
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- ✅ Performance monitoring and optimization
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- ✅ Agent-specific coaching strategies
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- ✅ Crisis management protocols
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- ✅ Motivation and morale management
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---
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## 📊 Comparison: Ralph vs. Our Integration
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| Aspect | Ralph (CLI Tool) | Our Integration (Patterns) |
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|---------|-----------------|---------------------------|
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| **Architecture** | Bash scripts + git loops | Claude Code agents with PROACTIVELY triggers |
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| **Memory** | Files + git state | Agent descriptions + shared context |
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| **Triggering** | Manual CLI execution | Automatic PROACTIVELY triggers |
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| **State** | `.ralph/` directory | Project files + agent memory |
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| **Use Case** | Autonomous multi-hour coding | Interactive development with humans |
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| **Installation** | `npm i -g @iannuttall/ralph` | Already in contains-studio agents |
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---
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||||
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## 🎯 Real-Life Example: Multi-Agent Project
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||||
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**User Request:** "Build a viral TikTok app in 2 weeks"
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### With Ralph (CLI Tool):
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```bash
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# User creates PRD JSON
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ralph prd
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# Ralph generates autonomous coding loop
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# User runs loop (takes hours)
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ralph build 25
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# Ralph autonomously:
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# - Writes code
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# - Commits to git
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# - Runs tests
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# - Iterates until done
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```
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### With Our Ralph-Inspired Agents:
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```bash
|
||||
# User makes request in Claude Code
|
||||
user: "Build a viral TikTok app in 2 weeks"
|
||||
|
||||
# studio-coach PROACTIVELY triggers
|
||||
[Coordinates all specialists]
|
||||
|
||||
studio-coach:
|
||||
├─► Frontend Developer: "Build React Native UI..."
|
||||
├─► Backend Architect: "Design scalable API..."
|
||||
├─► TikTok Strategist: "Plan viral features..."
|
||||
├─► Growth Hacker: "Design growth loops..."
|
||||
├─► Rapid Prototyper: "Build MVP in 2 days..."
|
||||
├─► Test Writer/Fixer: "Write comprehensive tests..."
|
||||
└─→ [Human in loop, user can guide at each step]
|
||||
|
||||
# Advantages:
|
||||
# - Human collaboration (not fully autonomous)
|
||||
# - Course correction at any time
|
||||
# - Clarification questions
|
||||
# - Design decisions involve user
|
||||
```
|
||||
|
||||
---
|
||||
|
||||
## 🤝 Why Not Use Ralph Directly?
|
||||
|
||||
Ralph is excellent for autonomous coding sessions, but our integration approach offers:
|
||||
|
||||
1. **Human-in-the-Loop:** You can guide, adjust, and collaborate
|
||||
2. **Real-Time Feedback:** Ask questions, clarify requirements mid-project
|
||||
3. **Design Collaboration:** Participate in creative decisions
|
||||
4. **Course Correction:** Pivot quickly based on new information
|
||||
5. **Interactive Development:** Not limited to pre-defined PRD
|
||||
|
||||
**Ralph Best For:**
|
||||
- Autonomous overnight coding sessions
|
||||
- Well-defined, pre-planned features
|
||||
- "Fire and forget" development
|
||||
- Large refactoring projects
|
||||
|
||||
**Our Agents Best For:**
|
||||
- Interactive development with user
|
||||
- Exploratory projects with evolving requirements
|
||||
- Creative collaboration
|
||||
- Design-heavy work requiring human input
|
||||
|
||||
---
|
||||
|
||||
## 📚 Summary
|
||||
|
||||
### What Ralph Provided:
|
||||
- ✅ Supervisor-agent coordination pattern
|
||||
- ✅ Task delegation frameworks
|
||||
- ✅ Shared context systems
|
||||
- ✅ Cross-agent workflow orchestration
|
||||
- ✅ Performance coaching strategies
|
||||
|
||||
### How We Applied Ralph Patterns:
|
||||
- ✅ **studio-coach** = Ralph's supervisor pattern
|
||||
- ✅ **studio-producer** = Ralph's task delegation pattern
|
||||
- ✅ **experiment-tracker** = Ralph's coordination pattern
|
||||
- ✅ Shared sprint context (6-day cycles)
|
||||
- ✅ Cross-functional workflows
|
||||
|
||||
### What We Didn't Copy:
|
||||
- ❌ Ralph's autonomous bash loops (we want human collaboration)
|
||||
- ❌ Ralph's git-as-memory system (we use agent context)
|
||||
- ❌ Ralph's PRD-driven approach (we want interactive flexibility)
|
||||
|
||||
---
|
||||
|
||||
## 🔗 Resources
|
||||
|
||||
- **[Ralph Framework](https://github.com/iannuttall/ralph)** - Original CLI tool
|
||||
- **[contains-studio/agents](https://github.com/contains-studio/agents)** - Our agent implementation
|
||||
- **[INTEGRATION-GUIDE.md](INTEGRATION-GUIDE.md)** - Technical integration details
|
||||
- **[CONTAINS-STUDIO-INTEGRATION.md](CONTAINS-STUDIO-INTEGRATION.md)** - PROACTIVELY auto-triggering
|
||||
|
||||
---
|
||||
|
||||
**Built for developers who ship.** 🚀
|
||||
@@ -894,6 +894,7 @@ Claude (as ui-ux-pro-max): I'll create a professional, accessible modal...
|
||||
- **[MASTER-PROMPT.md](MASTER-PROMPT.md)** - Copy-paste installation prompt for Claude Code
|
||||
- **[INTEGRATION-GUIDE.md](INTEGRATION-GUIDE.md)** - Technical integration details
|
||||
- **[CONTAINS-STUDIO-INTEGRATION.md](CONTAINS-STUDIO-INTEGRATION.md)** - PROACTIVELY auto-triggering explained
|
||||
- **[RALPH-INTEGRATION.md](RALPH-INTEGRATION.md)** - How Ralph framework patterns were integrated
|
||||
- **[CLAUDE-CUSTOMIZATIONS-README.md](CLAUDE-CUSTOMIZATIONS-README.md)** - Complete feature documentation
|
||||
- **[FINAL-SETUP-GUIDE.md](FINAL-SETUP-GUIDE.md)** - Detailed setup instructions
|
||||
- **[SCRIPTS-GUIDE.md](SCRIPTS-GUIDE.md)** - Script usage guide
|
||||
|
||||
Reference in New Issue
Block a user