Agent Orchestration & Security Template

A reference architecture for AI agent orchestration, trust measurement, and tool integration. Designed to be studied, forked, and adapted -- not contributed to directly. All code changes in this repository are authored by AI agents under human oversight. Browse the project showcase for an overview.

This repo demonstrates how to run a council of AI agents (Claude, OpenCode, Crush) across a shared codebase with board-driven task delegation, automated PR review, security hardening, and containerized tooling. (OpenAI/Google integrations have been disabled -- see security notice.) It also includes standalone research packages for sleeper agent detection, autonomous economic agent simulation, and tamper-responsive hardware. Several companion repositories consume or extend the functionality of this project.

Use this repo to learn how to:

• Orchestrate multiple AI agents with a GitHub Projects v2 work queue
• Measure and enforce trust boundaries for autonomous agents (wrapper guards, iteration limits, claim tracking)
• Integrate 20 MCP servers spanning code quality, content creation, 3D graphics, video editing, and speech synthesis
• Build hardened CI/CD pipelines for agent-authored code (15-stage pipeline, security scanning, multi-arch Docker builds)
• Detect sleeper agent behaviors via residual stream analysis and linear probes
• Integrate AI agents into legacy software via runtime injection, shared memory IPC, and overlay rendering

Important: This is an advanced template designed for experienced developers working with autonomous AI agents. Before diving in, we strongly recommend:

1. Read the AI Safety Training Guide - Essential concepts for safe human-AI collaboration, including deception detection, scalable oversight, and control protocols

2. Take an AI Safety course at BlueDot Impact - Free, rigorous training programs covering AI safety fundamentals, governance, and alignment

Working with AI agents introduces risks that differ fundamentally from traditional software. Understanding these risks isn't optional - it's a prerequisite for responsible development.

Legal Notice

This repository contains dual-use research and tooling. The maintainer provides no guidance, consultation, or feature development -- whether solicited or unsolicited, compensated or uncompensated. This policy exists as a legal protection given the nature of the codebase.

• No feature requests will be accepted. Money does not change this.
• No guidance or consulting will be provided on usage, adaptation, or deployment of any component.
• No external contributions are accepted. See CONTRIBUTING.md.
• The maintainer does not seek or engage with community interaction. Public comments, issues filed by external parties, events, and news surrounding this repository or its components may be ignored without response to maintain neutrality and legal distance.
• No endorsement is implied. The existence of code in this repository does not constitute encouragement, recommendation, or endorsement of any particular use.

This repository is released under a public domain dedication. You may fork and adapt it freely. The maintainer assumes no obligation to any downstream user for any reason.

Project Philosophy

This project follows a container-first approach:

• All tools and CI/CD operations run in Docker containers for maximum portability
• Zero external dependencies - runs on any Linux system with Docker
• Self-hosted infrastructure - no cloud costs, full control over runners
• Single maintainer design - optimized for individual developer productivity, no contributors model
• Modular MCP architecture - Separate specialized servers for different functionalities

Quick Start

New to the template? Check out our Template Quickstart Guide for step-by-step customization instructions!

1. Prerequisites: Linux system with Docker (v20.10+) and Docker Compose (v2.0+)

2. Clone and setup

   hljs language-bash

   Copy

   git clone https://github.com/AndrewAltimit/template-repo
   cd template-repo
   # Build the Rust CLI tools (optional - pre-built binaries available in releases)
   cd tools/rust/board-manager && cargo build --release
   cd ../github-agents-cli && cargo build --release
   

3. Set API keys (if using AI features)

   hljs language-bash

   Copy

   export OPENROUTER_API_KEY="your-key-here"  # For OpenCode/Crush
   

4. Use with Claude Code: MCP servers are configured in .mcp.json and auto-started by Claude. See MCP Configuration for essential vs full setups.

5. Run CI/CD operations

   hljs language-bash

   Copy

   automation-cli ci run full  # Full pipeline
   

For detailed setup, see CLAUDE.md and Template Quickstart Guide.

AI Agents

Six AI agents for development and automation. See AI Agents Documentation for details.

Security Notice -- OpenAI/Google Disabled: OpenAI/Google integrations are disabled within PR reviews. OpenAI/Google permits government partners unrestricted use of their models. We only allow models with explicit prohibitions on mass surveillance and autonomous weapons.

OpenCode and Crush provide equivalent code generation functionality via OpenRouter. Codex (OpenAI) and Gemini (Google) have been disabled -- see security notice above.

Security: Keyword triggers, user allow list, secure token management. See Security Model

Safety Training: Essential AI safety concepts for human-AI collaboration. See Human Training Guide

Sleeper Agents: Create and evaluate sleeper agents in order to detect misalignment and probe for deception. See Sleeper Agents Package

Agentic Git Workflow

AI agents autonomously manage the development lifecycle from issue creation through PR merge:

Issue Created → Admin Approval → Agent Claims → PR Created → AI Review → Human Merge

The Flow:

1. Issue Creation - Issues are created manually or by agents via backlog-refinement.yml, automatically added to the GitHub Projects board
2. Admin Approval - An authorized user comments [Approved][Claude] (or another agent name) to authorize work
3. Agent Claims - board-agent-worker.yml finds approved issues, the agent claims the issue and creates a working branch
4. Implementation - The agent implements the fix/feature and opens a PR
5. AI Review - pr-validation.yml triggers AI code review (Claude + OpenRouter); pr-review-monitor.yml lets agents iterate on feedback
6. Human Merge - Admin reviews and merges the PR

Security Model:

• Approval Required - Agents cannot work on issues without explicit [Approved][Agent] comment
• Authorized Users Only - Only users listed in .agents.yaml → security.agent_admins can approve
• Pattern Validation - Must use [Action][Agent] format (e.g., [Approved][Claude]) to prevent false positives
• Claim Tracking - Agents post claim comments with timestamps to prevent conflicts

See Security Documentation for the complete security model.

Reports & Research

Technical reports and guides exploring AI risks, safety frameworks, and philosophical questions. PDFs are automatically built from LaTeX source and published with each release.

Emerging Technology Risk Assessments

Scenario-based projection reports analyzing potential futures involving advanced AI systems. See Projections Documentation.

Technical Guides

Philosophy Papers

Philosophical explorations of minds, experience, and intelligence. See Philosophy Papers Documentation.

Build Status:

Packages

Standalone packages addressing different aspects of AI agent development, safety, and security:

Rust CLI Tools (in tools/rust/):

Companion Repositories

Companion repositories consume template-repo release binaries (e.g., github-agents-cli, automation-cli) for their AI-assisted workflows.

# Install Python packages
pip install -e ./packages/sleeper_agents

# Build Rust packages (requires Rust toolchain)
cd packages/economic_agents && cargo build --release
cd tools/rust/github-agents-cli && cargo build --release
cd tools/rust/board-manager && cargo build --release

Features

• 20 MCP Servers - Code quality, content creation, AI assistance, 3D graphics, video editing, speech synthesis, and more
• 6 AI Agents - Autonomous development workflow from issue to merge
• 4 Packages - Sleeper agent detection, economic agent simulation, tamper-responsive briefcase, CRISPR automation
• Container-First Architecture - Maximum portability and consistency
• Self-Hosted CI/CD - Zero-cost GitHub Actions infrastructure
• Company Integration - Corporate proxy builds for enterprise AI APIs (Docs)

Enterprise & Corporate Setup

For enterprise environments requiring custom certificates, customize automation/corporate-proxy/shared/scripts/install-corporate-certs.sh. This script runs during Docker builds for all containers. See the customization guide for details.

Project Structure

.
├── .github/workflows/        # GitHub Actions workflows
├── docker/                   # Docker configurations
├── packages/                 # Installable packages
│   ├── sleeper_agents/       # AI backdoor detection framework (Python)
│   ├── economic_agents/      # Autonomous economic agents (Rust)
│   ├── tamper_briefcase/     # Tamper-responsive briefcase system (Rust)
│   └── bioforge/             # Agent-driven CRISPR automation platform (Rust)
├── tools/
│   ├── mcp/                  # 20 MCP servers (see MCP Servers section)
│   ├── rust/                 # Rust CLI tools
│   │   ├── github-agents-cli/    # Issue/PR monitoring, refinement, analysis
│   │   ├── board-manager/        # GitHub Projects board operations
│   │   ├── git-guard/            # Git wrapper requiring sudo for dangerous ops
│   │   ├── gh-validator/         # Secret masking for GitHub CLI
│   │   ├── pr-monitor/           # PR feedback monitoring
│   │   ├── markdown-link-checker/ # Fast link validation for CI/CD
│   │   ├── code-parser/          # Parse code blocks from AI responses
│   │   └── mcp-code-quality/     # Rust MCP server for code quality
│   └── cli/                  # Agent runners and utilities
├── automation/               # CI/CD and automation scripts
├── tests/                    # Test files
├── docs/                     # Documentation
└── config/                   # Configuration files

MCP Servers

Available Servers

1. Code Quality - Formatting, linting, auto-formatting
2. Content Creation - Manim animations, LaTeX, TikZ diagrams
3. Gaea2 - Terrain generation (Documentation)
4. Blender - 3D content creation, rendering, physics simulation (Documentation)
5. Gemini - AI consultation DISABLED (Google -- security risk, see notice)
6. Codex - AI-powered code generation and completion DISABLED (OpenAI -- security risk, see notice)
7. OpenCode - Code generation via OpenRouter
8. Crush - Code generation via OpenRouter
9. Meme Generator - Create memes with templates
10. ElevenLabs Speech - Advanced TTS with v3 model, 50+ audio tags, 74 languages (Documentation)
11. Video Editor - AI-powered video editing with transcription and scene detection (Documentation)
12. Virtual Character - AI agent embodiment in virtual worlds (VRChat, Blender, Unity) (Documentation)
13. GitHub Board - GitHub Projects v2 board management, work claiming, agent coordination (Documentation)
14. AI Toolkit - LoRA training interface (remote: 192.168.0.222:8012)
15. ComfyUI - Image generation interface (remote: 192.168.0.222:8013)
16. Memory Explorer - Process memory exploration for agent integration with legacy software (Rust)
17. AgentCore Memory - Multi-provider AI memory (AWS AgentCore or ChromaDB) (Documentation)
18. Reaction Search - Semantic search for anime reaction images (Rust)
19. Desktop Control - Cross-platform desktop automation for Linux and Windows (Documentation)
20. Sprite Sheet - Programmatic pixel art and sprite sheet creation (Documentation)

Usage Modes

• STDIO Mode (local MCPs): Configured in .mcp.json, auto-started by Claude
• HTTP Mode (remote MCPs): Run the MCP using docker compose on the remote node.

See MCP Architecture Documentation and STDIO vs HTTP Modes for details.

Tool Reference

For complete tool listings, see MCP Tools Reference

Configuration

Environment Variables

See .env.example for all available options.

Key Configuration Files

• .mcp.json - MCP server configuration for Claude Code
• docker-compose.yml - Container services configuration
• CLAUDE.md - Project-specific Claude Code instructions (root directory)
• AGENTS.md - Universal AI agent configuration and guidelines (root directory)
• docs/agents/project-context.md - Context for AI reviewers

Setup Guides

• Self-Hosted Runner Setup
• GitHub Environments Setup
• Gemini Setup
• Containerized CI

Development Workflow

Container-First Development

All Python operations run in Docker containers:

# Run CI operations via automation-cli
automation-cli ci run format             # Check formatting
automation-cli ci run lint-basic         # Basic linting
automation-cli ci run test               # Run tests
automation-cli ci run full               # Full CI pipeline

# Run specific tests
docker compose run --rm python-ci pytest tests/test_mcp_tools.py -v

GitHub Actions

• Pull Request Validation - Automatic AI review via Claude + OpenRouter (Gemini and Codex reviews disabled)
• Continuous Integration - Full CI pipeline
• Code Quality - Multi-stage linting (containerized)
• Automated Testing - Unit and integration tests
• Security Scanning - Bandit and safety checks

All workflows run on self-hosted runners for zero-cost operation.

Documentation

Core Documentation

• AGENTS.md - Universal AI agent configuration and guidelines
• CLAUDE.md - Claude-specific instructions and commands
• MCP Architecture - Modular server design
• AI Agents Documentation - AI agents overview

Quick References

• AI Code Agents Quick Reference
• MCP Tools Reference
• Gaea2 Quick Reference

Integration Guides

• AI Code Agents Integration
• AI Toolkit & ComfyUI Integration
• Gaea2 Documentation

Setup & Configuration

• Template Quickstart Guide - Customize the template for your needs
• Self-Hosted Runner Setup
• GitHub Environments Setup
• Containerized CI

License

This project is released under the Unlicense (public domain dedication).

For jurisdictions that do not recognize public domain: As a fallback, this project is also available under the MIT License.

Disclaimer

This repository and all associated documentation, code, research papers, and tools are provided as-is with no warranty of any kind. The maintainer makes no representations regarding the suitability, legality, or safety of any component for any purpose. Users assume all responsibility for their use of this material.

The maintainer is not responsible for any use or misuse of the contents of this repository. No advisory, consulting, support, or guidance relationship is created by the publication of this code. The maintainer expressly disclaims any obligation to respond to inquiries, feature requests, bug reports, or other communications from any party.

Portions of this repository contain dual-use security research and tooling. Publication of this material is for defensive research, education, and policy analysis purposes. The maintainer does not endorse, encourage, or facilitate any unlawful use.