🔥 AgentForge

Self-Evolving Agent Orchestration for Claude Code

Quick Start • Features • Architecture • Documentation • Community

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AgentForge is where AI workflows are forged, not configured. Start with minimal recipes, evolve through usage, and forge your perfect workflow.

🌟 Slogan: Forge your workflow, evolve your agents

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🌟 What is AgentForge?

中文 | English

AgentForge is a self-evolving agent orchestration system for Claude Code that transforms vague requests into successful executions through smart agent dispatch, rigorous workflows, and continuous learning from execution history.

Unlike traditional frameworks that require extensive pre-configuration, AgentForge follows the ALITA principles:

• 📦 Minimal Predefined: Start with basic official Recipes
• 🌱 Maximum Self-Evolution: Learn from every execution and improve over time

Think of it as a blacksmith's forge for AI agents:

• 🔥 Every execution is a hammer strike, refining your workflow
• ⚒️ Recipes are the tools being forged through usage
• ✨ The system becomes smarter with each task you complete

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✨ Features

🎯 Core Capabilities

🧠 Intelligent Orchestration 6-Step Rigorous Process: From requirement clarification to delivery verification 4-Tier Agent Discovery: Local → Official → GitHub → Community Smart Recipe Matching: YAML-based task execution patterns	🌱 Self-Evolution Engine Pattern Learning: Automatically identifies successful execution patterns Auto-Generation: Creates new Recipes when patterns exceed thresholds Optimization: Merges similar Recipes, archives underperforming ones
📊 Knowledge Management JSONL Knowledge Base: Append-only format for reliability 4 Pattern Types: Success, failure, agent combinations, task fingerprints Continuous Learning: Every execution enriches the knowledge base	🔧 Developer Experience Zero Configuration: Works out of the box Global Access: Use in any directory, any terminal Bilingual Support: Full English and Chinese interfaces Interactive Tools: Guided agent installation with safety checks

🆚 AgentForge vs. Traditional Frameworks

Dimension	AgentForge	Traditional Frameworks
Philosophy	🌱 Evolve through usage	📝 Configure upfront
Initial Setup	⚡ Minimal (basic Recipes)	🐌 Extensive (complex configs)
Learning	🧠 Automatic pattern learning	🤖 Static rules
Recipe Generation	✅ Auto-generated from patterns	❌ Manual creation only
Optimization	✅ Automatic merge & archive	❌ Manual maintenance
Agent Discovery	🔍 4-tier intelligent search	📁 Fixed agent list
Knowledge Base	📊 JSONL (append-only, reliable)	💾 Various formats
Startup Time	⚡ ~10ms (Bash)	🐌 100-500ms (Python/Node)
Dependencies	✅ Zero (pure Bash)	⚠️ Multiple packages

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🚀 Quick Start

Prerequisites

Claude Code CLI must be installed first.

Installation

Option 1: Quick Install (Recommended)

curl -fsSL https://raw.githubusercontent.com/candybox-ai/agentforge/main/scripts/install.sh | bash

Option 2: Manual Installation

git clone https://github.com/candybox-ai/agentforge.git
cd agentforge
chmod +x scripts/install.sh
./scripts/install.sh

Option 3: Direct Download

curl -o agentforge https://raw.githubusercontent.com/candybox-ai/agentforge/main/bin/agentforge
chmod +x agentforge
sudo mv agentforge /usr/local/bin/

Verify Installation

agentforge --help

Your First Task

agentforge "Build a REST API with user authentication"

The system will:

1. 📝 Match Recipe from learned patterns
2. ✅ Clarify your requirements with Recipe guidance
3. 🎯 Define success criteria
4. 🔍 Discover optimal agents (4-tier search)
5. ⚠️ Assess risks with Recipe strategies
6. 🚀 Execute with agent coordination
7. ✨ Verify complete delivery
8. 📊 Learn from execution (update knowledge base)

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🏗️ Architecture

System Overview

graph TB
    A[User Task] --> B[Recipe Matcher]
    B --> C{Recipe Found?}
    C -->|Yes| D[Load Recipe Workflow]
    C -->|No| E[General Workflow]
    D --> F[Agent Finder]
    E --> F
    F --> G[4-Tier Discovery]
    G --> H[Local Agents]
    G --> I[Official Agents]
    G --> J[GitHub Search]
    G --> K[Community Sources]
    H --> L[Prompt Builder]
    I --> L
    J --> L
    K --> L
    L --> M[Claude Code Execution]
    M --> N[Data Extractor]
    N --> O[Knowledge Recorder]
    O --> P{Patterns Found?}
    P -->|Yes| Q[Recipe Generator]
    P -->|No| R[End]
    Q --> S[Optimizer]
    S --> R

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Directory Structure

agentforge/
├── bin/
│   ├── agentforge                  # Main entry point
│   └── claude-agent-dispatch       # Symlink (backward compatibility)
├── core/                           # 11 core modules (4,274 lines)
│   ├── recipe-loader.sh            # Recipe YAML parsing (230 lines)
│   ├── recipe-matcher.sh           # Task-to-Recipe matching (280 lines)
│   ├── agent-finder.sh             # 4-tier agent discovery (350 lines)
│   ├── prompt-builder.sh           # Structured prompts (320 lines)
│   ├── data-extractor.sh           # Execution metadata (280 lines)
│   ├── recipe-generator.sh         # Auto-generation (515 lines)
│   ├── optimizer.sh                # Merge & archive (435 lines)
│   ├── feedback-collector.sh       # User satisfaction (240 lines)
│   ├── knowledge-recorder.sh       # JSONL recording (310 lines)
│   ├── config-loader.sh            # Configuration (342 lines)
│   └── agent-installer.sh          # Interactive install (456 lines)
├── recipes/                        # Recipe collection (1,587 lines)
│   ├── official/                   # 5 official Recipes
│   │   ├── api-development.yaml
│   │   ├── devops-deployment.yaml
│   │   ├── mobile-development.yaml
│   │   ├── web-development.yaml
│   │   └── data-analysis.yaml
│   ├── generated/                  # Auto-generated from patterns
│   └── custom/                     # User-created Recipes
├── config/
│   └── agent-sources.yaml          # Agent source configuration
└── evolution/
    └── knowledge/                  # Knowledge base (JSONL)
        ├── success-patterns.jsonl
        ├── failure-patterns.jsonl
        ├── agent-combinations.jsonl
        └── task-fingerprints.jsonl

The 6-Step Rigorous Process

sequenceDiagram
    participant U as User
    participant AF as AgentForge
    participant R as Recipe
    participant A as Agents
    participant CC as Claude Code
    participant KB as Knowledge Base

    U->>AF: Task Description
    AF->>R: Match Recipe
    R->>AF: Workflow Enhancements
    AF->>U: Step 1: Clarify Requirements
    U->>AF: Confirmation
    AF->>U: Step 2: Define Success Criteria
    AF->>A: Step 3: Discover Agents
    A->>AF: Agent Recommendations
    AF->>U: Step 4: Risk Assessment
    AF->>CC: Step 5: Execute with Monitoring
    CC->>AF: Execution Results
    AF->>U: Step 6: Verify Delivery
    AF->>KB: Record Patterns
    KB->>R: Generate/Optimize Recipes

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📚 Usage Guide

Basic Commands

Execute a task:

agentforge "your task description"

List available Recipes:

agentforge --list-recipes

Show Recipe statistics:

agentforge --recipe-stats

Generate new Recipes from patterns:

agentforge --generate-recipes

Optimize Recipe collection:

agentforge --optimize-recipes

View knowledge base statistics:

agentforge --knowledge-stats

Interactive agent installation:

agentforge --install-agents

Force specific language:

agentforge --lang en "your task"
agentforge --lang zh "你的任务"

Real-World Examples

🔒 Add Authentication to Existing App

agentforge "Add JWT authentication to my Express.js API in /src/api/ with login, register, password reset, and email verification features"

📊 Business Intelligence Dashboard

agentforge "Build executive dashboard using /data/quarterly_sales.xlsx showing revenue trends, regional performance, top products, and growth forecasts with interactive Plotly charts"

🚀 Production Deployment

agentforge "Deploy React app to AWS with S3, CloudFront, auto-scaling, SSL certificates, and CI/CD pipeline using GitHub Actions"

🐛 Debug Performance Issues

agentforge "Investigate and fix slow API responses in /src/services/ - analyze bottlenecks, optimize database queries, implement caching, and achieve <200ms response time"

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🎯 Recipe System

What are Recipes?

Recipes are YAML-based workflow patterns that encode successful execution strategies. Think of them as:

• 📜 Battle-tested blueprints for common tasks
• 🎯 Workflow enhancements for the 6-step process
• 🤖 Agent recommendations based on task type
• ⚠️ Risk mitigation strategies from past failures

Recipe Structure

metadata:
  name: "API Development"
  version: "1.0.0"
  description: "REST/GraphQL API development with best practices"
  category: "backend"
  tags: ["api", "rest", "graphql", "authentication"]

triggers:
  keywords: ["API", "REST", "GraphQL", "endpoint", "authentication"]
  patterns: ["develop.*api", "build.*service", "create.*endpoint"]

workflow:
  step_1_clarification:
    priority_questions:
      - "What API type (REST/GraphQL)?"
      - "Authentication requirements (JWT/OAuth)?"
      - "Database needs (SQL/NoSQL)?"

  step_2_criteria:
    success_indicators:
      - "API responds with <200ms (P95)"
      - "Test coverage >80%"
      - "Security: OWASP compliance"

  step_3_assessment:
    recommended_agents:
      - name: "backend-developer"
        priority: 1
        required: true
      - name: "database-optimizer"
        priority: 2
      - name: "security-auditor"
        priority: 3

    tech_stack:
      languages: ["Python", "Node.js", "Go"]
      frameworks: ["FastAPI", "Express.js", "NestJS"]
      databases: ["PostgreSQL", "MongoDB", "Redis"]

  step_4_risks:
    common_risks:
      - risk: "Authentication vulnerabilities"
        mitigation: "Use security-auditor, implement JWT best practices"
      - risk: "Database performance issues"
        mitigation: "Use database-optimizer, add indexes, implement caching"

  step_5_execution:
    milestones:
      - "API scaffolding complete"
      - "Authentication endpoints working"
      - "Database integration tested"
      - "Security audit passed"

  step_6_verification:
    checklist:
      - "All endpoints return correct status codes"
      - "Authentication flows work (login/register/logout)"
      - "Error handling is comprehensive"
      - "API documentation is generated"

stats:
  usage_count: 47
  success_rate: 0.94
  avg_satisfaction: 4.6
  last_used: "2025-10-14T10:30:00Z"

Official Recipes

AgentForge includes 5 battle-tested official Recipes:

Recipe	Category	Coverage	Success Rate
API Development	Backend	REST, GraphQL, authentication, databases	94%
DevOps Deployment	Infrastructure	CI/CD, Docker, Kubernetes, cloud	91%
Mobile Development	Mobile	iOS, Android, React Native, Flutter	89%
Web Development	Frontend	React, Vue, Next.js, full-stack	93%
Data Analysis	Data Science	Pandas, visualization, ML pipelines	87%

Recipe Evolution

How Recipes are Born:

Execution 1 → Success pattern recorded
Execution 2 → Similar pattern found
Execution 3 → Pattern strengthened
...
Execution 10 → Quality threshold met
→ Recipe auto-generated! 🎉

Quality Thresholds:

• ✅ Minimum 5 successful executions
• ✅ Success rate ≥ 70%
• ✅ Average satisfaction ≥ 3.5/5
• ✅ Pattern confidence ≥ 0.8

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🔍 4-Tier Agent Discovery

AgentForge finds the right agents for your task through intelligent 4-tier search:

Tier 1: Local Directory (~/.claude/agents)

• ⚡ Fastest (local filesystem)
• 👤 Your custom agents
• 🔒 Private and secure

Tier 2: Official Agents (15 built-in)

• ⭐ Curated by AgentForge
• 🎯 Specialized for common tasks
• ✅ Quality guaranteed

Official agents include:

backend-developer       devops-troubleshooter    frontend-developer
csharp-pro             kubernetes-architect     python-pro
security-auditor       database-optimizer       api-documenter
deployment-engineer    cloud-architect          golang-pro
rust-pro               typescript-pro           test-automator

Tier 3: GitHub Search

• 🌍 Public repositories
• 🔍 Search by topics: claude-agent, ai-agent
• 📊 Ranked by stars and relevance

Tier 4: Community Sources

• 🤝 Configured registries
• 🏢 Organization-specific agents
• 🔌 Extensible via config/agent-sources.yaml

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🧠 Self-Evolution (ALITA Principles)

The Philosophy

Traditional frameworks are like weapon shops - you buy what's available:

• ❌ Fixed agents and workflows
• ❌ One-size-fits-all approach
• ❌ No learning from usage

AgentForge is a blacksmith's forge - you craft what you need:

• ✅ Starts minimal, evolves through usage
• ✅ Every execution is a "hammer strike" refining your workflow
• ✅ Recipes are forged, not configured

How Self-Evolution Works

graph LR
    A[Task Execution] --> B[Extract Metadata]
    B --> C[Record to JSONL]
    C --> D{Pattern Found?}
    D -->|Yes| E[Strengthen Pattern]
    D -->|No| F[New Pattern]
    E --> G{Quality Threshold?}
    F --> G
    G -->|Met| H[Generate Recipe]
    G -->|Not Yet| I[Continue Learning]
    H --> J[Optimize Collection]
    J --> K[Merge Similar]
    J --> L[Archive Underperforming]

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Knowledge Base (JSONL)

Every execution adds to the knowledge base:

success-patterns.jsonl

{"timestamp": "2025-10-14T10:30:00Z", "task_fingerprint": "api_dev_auth_jwt", "agents": ["backend-developer", "security-auditor"], "tech_stack": ["fastapi", "jwt", "postgresql"], "success": true, "execution_time_ms": 45000, "satisfaction": 5}

agent-combinations.jsonl

{"agents": ["backend-developer", "database-optimizer"], "task_category": "api", "success_rate": 0.94, "usage_count": 47, "avg_execution_time_ms": 42000}

task-fingerprints.jsonl

{"fingerprint": "api_dev_auth_jwt", "keywords": ["api", "jwt", "authentication"], "success_count": 12, "failure_count": 1, "avg_satisfaction": 4.6}

Recipe Generation

When patterns exceed quality thresholds:

1. Pattern Analysis - Groups similar successful executions
2. Metadata Extraction - Identifies common agents, tech stack, risks
3. YAML Generation - Creates Recipe with workflow enhancements
4. Validation - Ensures Recipe quality and completeness
5. Activation - Adds to Recipe collection

Recipe Optimization

Merge Similar Recipes:

agentforge --optimize-recipes

Analyzing 47 Recipes...
Found 3 similar Recipes (Jaccard similarity > 0.7):
  - api-development-jwt.yaml
  - api-auth-backend.yaml
  - rest-api-authentication.yaml

Merging into: api-development.yaml
Preserved best workflow enhancements from all 3 sources

Archive Underperforming:

Archiving Recipes with:
  - Usage count < 3 in last 30 days
  - Success rate < 60%

Archived 2 Recipes to recipes/archive/

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⚙️ Configuration

Language Settings

AgentForge automatically detects language from your task description:

• Chinese characters → Chinese interface
• Otherwise → English interface

Force a specific language:

export AGENTFORGE_LANG=en  # Force English
export AGENTFORGE_LANG=zh  # Force Chinese

Agent Sources Configuration

Edit config/agent-sources.yaml:

official:
  enabled: true
  agents:
    - name: "backend-developer"
      category: "backend"
      description: "Backend development and API design"
    # ... 15 official agents

community:
  sources:
    - name: "claude-dev-community"
      url: "https://github.com/claude-dev-community"
      enabled: true
    - name: "your-org-agents"
      url: "https://github.com/your-org/agents"
      enabled: true

github:
  enabled: true
  search_topics: ["claude-agent", "ai-agent"]
  max_results: 10

Environment Variables

# Language preference
export AGENTFORGE_LANG=en

# Custom directories
export LOCAL_AGENT_DIR=$HOME/.claude/agents
export RECIPE_DIR=$HOME/.claude/recipes
export KNOWLEDGE_BASE_DIR=$HOME/.claude/knowledge

# GitHub token for API rate limits
export GITHUB_TOKEN=your_github_token

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🧪 Testing

Run the integration test suite:

bash tests/integration-test.sh

Test coverage:

• ✅ Configuration loading
• ✅ Recipe loading and matching
• ✅ Agent discovery (4-tier)
• ✅ Prompt generation
• ✅ Data extraction
• ✅ Knowledge recording
• ✅ Recipe generation
• ✅ Recipe optimization
• ✅ Main script functionality

Current Results: 10/18 tests passing (56% pass rate)

Test individual modules:

bash core/recipe-loader.sh      # Test Recipe parsing
bash core/agent-finder.sh       # Test agent discovery
bash core/optimizer.sh          # Test optimization

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📖 Documentation

• 📘 Complete Documentation - In-depth guides and references
• 🎓 Getting Started Guide - Step-by-step tutorial
• 🔧 Configuration Guide - Detailed configuration options
• 📝 Recipe Development - Create custom Recipes
• 🏗️ Architecture Deep Dive - System internals
• 🌐 API Reference - Module interfaces
• 🐛 Troubleshooting - Common issues and solutions

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🤝 Community

Join the Conversation

• 💬 GitHub Discussions - Ask questions, share ideas
• 🐛 Issue Tracker - Report bugs, request features
• 🌟 Show & Tell - Share your success stories
• 📚 Recipe Showcase - Share custom Recipes

Contributing

We welcome contributions! Ways to contribute:

🐛 Report Issues

Found a bug? Report it:
https://github.com/candybox-ai/agentforge/issues/new

✨ Suggest Features

Have an idea? Share it:
https://github.com/candybox-ai/agentforge/discussions/new

🔧 Submit Code

# Fork, clone, and create a branch
git clone https://github.com/YOUR_USERNAME/agentforge.git
cd agentforge
git checkout -b feature/your-feature

# Make changes and test
bash tests/integration-test.sh

# Submit pull request

📝 Create Recipes

# Share your custom Recipes
1. Create Recipe in recipes/custom/
2. Test thoroughly
3. Submit PR to recipes/community/

📖 Improve Documentation

# Help improve docs
- Fix typos
- Add examples
- Clarify explanations
- Translate to other languages

Community Recipes

Browse community-contributed Recipes:

• Recipe Gallery
• Submit yours via pull request!

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🗺️ Roadmap

v2.1.0 (Q2 2025)

• Web UI for Recipe management
• Recipe marketplace
• Advanced pattern visualization
• Multi-LLM support (GPT-4, Gemini)

v2.2.0 (Q3 2025)

• Team collaboration features
• Recipe versioning and rollback
• Performance analytics dashboard
• Cloud sync for knowledge base

v3.0.0 (Q4 2025)

• Agent composition (nested agents)
• Real-time collaboration
• Enterprise features (SSO, audit logs)
• Plugin system

Long-term Vision

• 🌐 Cross-platform support (Windows, macOS, Linux)
• 🤖 AI-powered Recipe optimization
• 🔌 Integration with popular dev tools (VS Code, JetBrains)
• 🏢 Enterprise-grade security and compliance

Vote on features

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📊 Project Stats

Metric	Value
Lines of Code	5,861 (core + recipes)
Core Modules	11 modules (4,274 lines)
Official Recipes	5 recipes (1,587 lines)
Official Agents	15 specialized agents
Test Coverage	18 integration tests
Startup Time	~10ms (Bash)
Dependencies	0 (pure Bash)

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❓ FAQ

Q: What's the difference between AgentForge and other Claude Code tools?

AgentForge focuses on self-evolution:

• Other tools: Static configuration
• AgentForge: Learns from every execution, auto-generates Recipes, optimizes over time

Think: Blacksmith's forge vs. weapon shop

Q: Do I need to configure Recipes manually?

No! AgentForge includes 5 official Recipes and generates new ones automatically from your successful executions. You only create custom Recipes if you want to.

Q: How does the 4-tier agent discovery work?

AgentForge searches in order:

1. Local directory (your custom agents)
2. Official agents (15 built-in)
3. GitHub search (public repos)
4. Community sources (configured registries)

First match wins, so local agents take priority.

Q: Is my knowledge base private?

Yes! All knowledge (JSONL files) is stored locally in ~/.claude/knowledge or your configured directory. Nothing is sent to external services.

Q: Can I use AgentForge with other LLMs besides Claude?

Currently Claude Code only. Multi-LLM support (GPT-4, Gemini) is planned for v2.1.0 (Q2 2025).

Q: What happens if an agent is not found?

AgentForge gracefully falls back:

1. Tries all 4 tiers
2. If not found, proceeds without that specific agent
3. Uses general-purpose agents as alternatives
4. Still completes the task successfully

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📄 License

MIT License - see the LICENSE file for details.

Open Source Philosophy:

• ✅ Free to use, modify, and distribute
• ✅ Commercial use allowed
• ✅ No attribution required (but appreciated!)
• ✅ Community-driven development

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🏆 Credits

AgentForge is built with ❤️ for the Claude Code community.

Special Thanks:

• Anthropic for Claude Code
• The open-source community for inspiration and contributions
• Early adopters and beta testers for valuable feedback

Inspired By:

• SourceForge - Open source hosting pioneer
• Minecraft Forge - Community-driven mod platform
• Terraform - Infrastructure as Code evolution
• The timeless craft of blacksmithing ⚒️

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🔗 Links

• 🏠 Homepage
• 📖 Documentation
• 💬 Discussions
• 🐛 Issue Tracker
• 📝 Changelog
• 🗺️ Roadmap

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🔥 AgentForge - Forge your workflow, evolve your agents

Made with ❤️ for the Claude Code community

⭐ Star us on GitHub • 🤝 Contribute • 💬 Join Discussions