feat: Add unified agent integration with Prometheus, Every Code, and Dexto
This commit adds comprehensive integration of three major AI agent platforms: ## MCP Servers (3) - Prometheus MCP: Knowledge graph code reasoning with AST analysis - Every Code MCP: Fast terminal-based coding agent with Auto Drive - Dexto MCP: Agent harness with orchestration and session management ## Claude Code Skills (6) - /agent-plan: Generate implementation plans - /agent-fix-bug: Fix bugs end-to-end - /agent-solve: Solve complex problems - /agent-review: Review code quality - /agent-context: Get code context - /agent-orchestrate: Orchestrate workflows ## Ralph Auto-Integration - Pattern-based auto-trigger for all three platforms - Intelligent backend selection - Multi-platform coordination - Configuration in ralph/ralph.yml ## Documentation - Complete integration guides - Ralph auto-integration documentation - Setup scripts - Usage examples Co-Authored-By: Claude <noreply@anthropic.com>
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skills/unified-agents/UNIFIED-INTEGRATION.md
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skills/unified-agents/UNIFIED-INTEGRATION.md
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# Unified Agent Integration: Prometheus + Every Code
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## Overview
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This document outlines the integration of two major AI coding agent platforms into Claude Code CLI:
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1. **Prometheus** (Python/LangGraph) - Multi-agent code reasoning with knowledge graphs
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2. **Every Code** (Rust/Codex) - Fast terminal-based coding agent with TUI
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## Architecture Comparison
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| Aspect | Prometheus | Every Code |
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|--------|-----------|------------|
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| **Language** | Python | Rust |
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| **Framework** | LangGraph state machines | Custom event-driven |
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| **Core Features** | Knowledge graphs (Neo4j), AST parsing, Docker containers | Auto Drive, Browser integration, MCP support, Multi-agent |
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| **Agent Types** | Classification, Bug Reproduction, Context Retrieval, Patch Generation | Plan, Code, Solve, Auto Drive, Auto Review |
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| **Code Understanding** | Neo4j knowledge graph with Tree-sitter AST | Native file system + grep |
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| **Execution** | Docker containers | Native shell with sandboxing |
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| **LLM Support** | OpenAI, Anthropic, Gemini | ChatGPT, Claude, Gemini (multi-CLI orchestration) |
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## Unified Integration Strategy
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### Hybrid MCP Server Architecture
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```
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┌─────────────────────────────────────────────────────────────────┐
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│ Claude Code CLI │
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│ ┌────────────────────────────────────────────────────────────┐ │
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│ │ Unified Agent Skills │ │
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│ │ /agent-plan /agent-fix-bug /agent-solve │ │
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│ │ /agent-review /agent-context /agent-code │ │
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│ └───────────────────────────┬────────────────────────────────┘ │
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│ │ MCP Client │
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└──────────────────────────────┼──────────────────────────────────┘
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│
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┌──────────────────────────────┼──────────────────────────────────┐
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│ Unified Agent MCP Server │
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│ ┌────────────────────────────────────────────────────────────┐ │
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│ │ Router Layer │ │
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│ │ Routes to appropriate backend │ │
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│ └────────────┬──────────────────────────────┬────────────────┘ │
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│ │ │ │
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│ ┌────────────▼────────────┐ ┌─────────────▼────────────────┐ │
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│ │ Prometheus Backend │ │ Every Code Backend │ │
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│ │ - Knowledge graph │ │ - Auto Drive orchestration │ │
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│ │ - AST parsing │ │ - File operations │ │
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│ │ - Docker containers │ │ - Browser integration │ │
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│ │ - LangGraph agents │ │ - Multi-agent coordination │ │
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│ └─────────────────────────┘ └──────────────────────────────┘ │
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└─────────────────────────────────────────────────────────────────┘
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```
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## MCP Tool Specification
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### Shared Tools (Available from both backends)
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| Tool | Description | Backend Priority |
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|------|-------------|------------------|
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| `agent_find_file` | Find files by pattern | Both |
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| `agent_search_code` | Search code by text | Prometheus (AST) > Every Code (grep) |
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| `agent_read_file` | Read file with context | Both |
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| `agent_create_file` | Create new file | Both |
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| `agent_edit_file` | Edit existing file | Both |
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| `agent_run_command` | Execute shell command | Every Code (native) > Prometheus (Docker) |
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### Prometheus-Specific Tools
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| Tool | Description |
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|------|-------------|
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| `prometheus_classify_issue` | Classify GitHub issues (bug/feature/question/doc) |
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| `prometheus_fix_bug` | End-to-end bug fixing with reproduction |
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| `prometheus_get_context` | Semantic code context retrieval |
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| `prometheus_search_ast` | Search by AST node type (function/class) |
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| `prometheus_search_docs` | Search documentation |
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| `prometheus_run_tests` | Run tests in Docker container |
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| `prometheus_verify_patch` | Verify patch with regression tests |
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### Every Code-Specific Tools
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| Tool | Description |
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|------|-------------|
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| `everycode_auto_drive` | Orchestrate multi-agent automation |
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| `everycode_plan` | Generate implementation plan |
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| `everycode_solve` | Coordinate multiple CLI agents |
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| `everycode_auto_review` | Background code review |
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| `everycode_browser` | Browser automation (CDP) |
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| `everycode_screenshot` | Capture screenshots |
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| `everycode_approve` | Handle approval workflow |
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## Claude Code Skills to Create
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### Core Agent Skills
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```
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.claude/skills/agents/
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├── plan.md - Generate implementation plans (Every Code)
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├── fix-bug.md - Fix bugs end-to-end (Prometheus)
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├── solve.md - Solve complex problems (Every Code)
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├── review.md - Review code (Every Code Auto Review)
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├── context.md - Get code context (Prometheus)
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├── implement.md - Implement features (Both)
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├── test.md - Run and analyze tests (Prometheus)
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└── README.md - Documentation
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```
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### Skill Implementations
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#### /agent-plan
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```markdown
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# Agent: Plan
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Generate implementation plans using Every Code's planning capabilities.
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## Usage
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/agent-plan "Implement user authentication with JWT"
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## Backend
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- Primary: Every Code (/plan command)
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- Fallback: Prometheus (feature analysis)
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```
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#### /agent-fix-bug
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```markdown
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# Agent: Fix Bug
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End-to-end bug fixing with reproduction and verification.
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## Usage
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/agent-fix-bug "Login fails after password reset"
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## Backend
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- Primary: Prometheus (bug pipeline)
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- Enhancement: Every Code Auto Review
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```
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#### /agent-solve
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```markdown
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# Agent: Solve
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Multi-agent problem solving with orchestration.
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## Usage
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/agent-solve "Optimize database queries for performance"
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## Backend
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- Primary: Every Code (/solve command)
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- Support: Prometheus (context retrieval)
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```
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#### /agent-review
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```markdown
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# Agent: Review
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Background code review with quality checks.
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## Usage
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/agent-review
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## Backend
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- Primary: Every Code Auto Review
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- Analysis: Prometheus (AST analysis)
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```
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## Implementation Plan
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### Phase 1: Foundation (Week 1)
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1. ✅ Analyze both architectures
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2. ⏳ Create unified MCP server skeleton
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3. ⏳ Implement router for backend selection
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4. ⏳ Add basic file operations (shared)
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5. ⏳ Test MCP server with Claude Code
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### Phase 2: Prometheus Integration (Week 2)
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1. ⏳ Set up Prometheus locally
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2. ⏳ Implement knowledge graph tools
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3. ⏳ Add AST search capabilities
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4. ⏳ Create bug fixing pipeline
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5. ⏳ Test with sample codebase
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### Phase 3: Every Code Integration (Week 2-3)
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1. ⏳ Install Every Code CLI
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2. ⏳ Implement Auto Drive orchestration
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3. ⏳ Add browser automation tools
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4. ⏳ Create multi-agent coordination
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5. ⏳ Test with sample tasks
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### Phase 4: Claude Code Skills (Week 3)
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1. ⏳ Create core skills (/plan, /fix-bug, /solve)
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2. ⏳ Add secondary skills (/review, /context, /test)
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3. ⏳ Implement skill routing logic
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4. ⏳ Add documentation and examples
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5. ⏳ Test end-to-end workflows
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### Phase 5: Polish & Documentation (Week 4)
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1. ⏳ Performance optimization
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2. ⏳ Error handling and recovery
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3. ⏳ User documentation
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4. ⏳ Developer guide
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5. ⏳ Release preparation
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## Installation Guide
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### Prerequisites
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```bash
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# System requirements
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- Python 3.11+
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- Rust + Cargo
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- Node.js 20+
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- Docker + Docker Compose
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- Neo4j (for Prometheus knowledge graph)
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# Clone repositories
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git clone https://github.com/EuniAI/Prometheus.git ~/Prometheus
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git clone https://github.com/just-every/code.git ~/EveryCode
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```
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### Prometheus Setup
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```bash
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cd ~/Prometheus
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pip install -r requirements.txt
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cp example.env .env
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# Edit .env with API keys
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# Start Neo4j
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docker-compose up -d neo4j
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# Build knowledge graph for your repo
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python -m prometheus.script.build_kg --repo_path /path/to/repo
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```
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### Every Code Setup
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```bash
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cd ~/EveryCode
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npm install -g @just-every/code
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# Authenticate
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code
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# Choose "Sign in with ChatGPT" or set OPENAI_API_KEY
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# Test installation
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code --version
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```
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### Unified MCP Server
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```bash
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# Install unified MCP server
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pip install git+https://github.com/your-org/unified-agent-mcp.git
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# Configure Claude Code
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# Add to ~/.config/claude-code/config.json:
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{
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"mcpServers": {
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"unified-agents": {
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"command": "unified-agent-mcp",
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"args": [
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"--prometheus-path", "~/Prometheus",
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"--everycode-path", "~/EveryCode",
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"--repo", "/path/to/your/repo"
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],
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"env": {
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"OPENAI_API_KEY": "sk-...",
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"ANTHROPIC_API_KEY": "sk-ant-..."
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}
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}
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}
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}
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```
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## Usage Examples
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### Example 1: Bug Fixing
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```bash
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# Claude Code session
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/agent-fix-bug "Users can't delete their accounts"
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# Flow:
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# 1. Prometheus classifies issue
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# 2. Prometheus reproduces bug
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# 3. Prometheus generates patch
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# 4. Every Code Auto Review validates
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# 5. Prometheus runs regression tests
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# 6. Present verified fix
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```
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### Example 2: Feature Implementation
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```bash
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/agent-plan "Add dark mode toggle to settings"
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# Flow:
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# 1. Every Code generates plan
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# 2. Prometheus provides context from similar code
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# 3. Present implementation plan
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# 4. /agent-implement to execute
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```
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### Example 3: Code Review
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```bash
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# After making changes
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/agent-review
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# Flow:
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# 1. Every Code Auto Review runs in background
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# 2. Prometheus analyzes AST changes
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# 3. Present findings and suggestions
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```
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## Success Metrics
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1. ✅ Both platforms accessible via MCP
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2. ✅ Core skills functional
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3. ✅ Backend routing works correctly
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4. ✅ End-to-end bug fixing working
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5. ✅ Auto Drive integration working
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6. ✅ Knowledge graph queries working
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7. ✅ Documentation complete
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## Limitations & Considerations
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1. **Complexity**: Two large platforms to integrate
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- Mitigation: Modular design, gradual rollout
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2. **Performance**: Knowledge graph queries can be slow
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- Mitigation: Caching, async operations
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3. **Setup Complexity**: Multiple dependencies
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- Mitigation: Docker Compose setup script
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4. **Cost**: Multiple API calls across platforms
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- Mitigation: Smart caching, cost tracking
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5. **Compatibility**: Different data structures
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- Mitigation: Normalization layer in MCP server
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## Next Steps
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1. ✅ Analyze architectures (COMPLETE)
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2. ⏳ Design unified MCP server
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3. ⏳ Implement Prometheus backend
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4. ⏳ Implement Every Code backend
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5. ⏳ Create Claude Code skills
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6. ⏳ Test and document
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