valora.ai
Health Warn
- No license — Repository has no license file
- Description — Repository has a description
- Active repo — Last push 0 days ago
- Community trust — 17 GitHub stars
Code Fail
- rm -rf — Recursive force deletion command in .devcontainer/prepare-terminal.sh
Permissions Pass
- Permissions — No dangerous permissions requested
This tool is an orchestration platform that coordinates a network of specialized AI agents to automate the entire software development lifecycle. It handles everything from initial planning and architecture to code generation and deployment validation.
Security Assessment
Overall Risk: Medium. The repository contains a `rm -rf` recursive force deletion command inside a development container script (`.devcontainer/prepare-terminal.sh`). While often used for cleaning up build artifacts, recursive force deletions can be dangerous if a path variable is ever empty or undefined, potentially wiping critical system files. The tool does not request explicitly dangerous base permissions. Because it is designed to orchestrate software development, expect it to execute shell commands, make network requests to external LLM APIs (OpenAI, Anthropic, Google), and access your local file system heavily to read and write project code. No hardcoded secrets were detected.
Quality Assessment
The project appears to be actively maintained, with the most recent code push occurring today. It has a small but growing level of community trust, evidenced by 17 GitHub stars. However, there is a major legal and usage concern: the repository lacks a formal license file. Despite the README displaying an "MIT" badge, the actual repository has no license terms defined, which technically means default restrictive copyright laws apply. This absence makes it legally risky to use, modify, or distribute in commercial or open-source projects.
Verdict
Use with caution due to a dangerous recursive deletion command in a script and the complete absence of a software license.
VALORA (Versatile Agent Logic for Orchestrated Response Architecture) - The future of software development is not about replacing developers, but amplifying their capabilities with intelligent AI collaboration
VALORA
The future of software development is not about replacing developers, but amplifying their capabilities with intelligent AI collaboration.
Features • Quick Start • Architecture • Commands • Documentation
🏛️ About VALORA
VALORA (Versatile Agent Logic for Orchestrated Response Architecture) is a next-generation TypeScript-based platform designed to orchestrate a sophisticated network of AI agents to automate the complete software development lifecycle. By moving beyond simple "code generation", VALORA manages the delicate interplay between requirements, architecture, and deployment. VALORA provides intelligent automation while maintaining human oversight.
Why VALORA?
Intelligent Orchestration: VALORA coordinates 11 specialised AI agents, from @lead technical oversight to @secops-engineer compliance, ensuring the right expert is assigned to every task.
Three-Tier Flexibility: The engine adapts to your resources, offering MCP Sampling, Guided Completion, or API Fallback modes.
Phased Governance: Every project follows a rigorous 8-phase lifecycle, moving from initialisation and planning through implementation to validation and PR creation.
Strategic Optimisation: To balance depth and speed, VALORA assigns specific LLMs (like GPT-5 for planning or Claude Haiku for validation) based on the task's complexity.
VALORA is not a replacement for the developer; it is the high-fidelity instrument through which the developer conducts a full symphony of AI agents.
✨ Features
🤖 Multi-Agent Collaboration11 specialised AI agents with distinct expertise:
|
⚡ Three-Tier ExecutionFlexible execution modes for every use case:
*When available in Cursor Zero configuration required — works immediately with your Cursor subscription. |
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💎 Model OptimisationStrategic AI model assignment for cost efficiency:
31% strategic • 31% execution • 38% fast |
🔒 Security & ComplianceEnterprise-grade security controls:
|
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🌳 Worktree Dashboard & StatisticsLive visibility into parallel explorations:
|
🔌 External MCP IntegrationConnect to 15 external MCP servers with user approval:
|
🚀 Quick Start
Prerequisites
- Node.js 18+
Installation
# Install globally
pnpm add -g @windagency/valora # pnpm
yarn global add @windagency/valora # yarn
npm install -g @windagency/valora # npm
# Verify installation
valora --version
# Should output: 2.3.1
Project Setup
Initialise VALORA in your project:
cd your-project
valora init # Minimal setup (.valora/config.json)
valora init --full # Full setup with override directories
Your First Command
# Create an implementation plan
valora plan "Add user authentication with OAuth"
The engine will:
- Select the appropriate agent (
@lead) - Gather codebase context
- Generate a detailed implementation plan
- Provide step-by-step guidance
Zero-Config Usage with Cursor subscription
No API keys? No problem. The engine works immediately using Guided Completion Mode:
valora plan "Add dark mode toggle"
# → Generates structured prompt for Cursor AI
# → Uses your Cursor subscription (free)
Optional: API Configuration
For fully autonomous execution with cloud providers:
valora config setup --quick
# Or set environment variables
export ANTHROPIC_API_KEY=sk-ant-...
export OPENAI_API_KEY=sk-...
Optional: Local Models (No API Key)
Run fully offline with Ollama or any OpenAI-compatible server:
# Install and start Ollama
ollama pull llama3.1
ollama serve
# Use it directly
valora plan "Add auth" --provider local --model llama3.1
# Or configure as default
export LOCAL_BASE_URL=http://localhost:11434/v1
export LOCAL_DEFAULT_MODEL=llama3.1
🏗️ Architecture
┌─────────────────────────────────────────────────────────────────────────┐
│ VALORA │
├─────────────────────────────────────────────────────────────────────────┤
│ │
│ ┌─────────────┐ ┌──────────────┐ ┌─────────────┐ ┌─────────────┐ │
│ │ CLI Layer │ │ Orchestrator │ │ Agent Layer │ │ LLM Layer │ │
│ │ │──│ │──│ │──│ │ │
│ │ • Commands │ │ • Pipeline │ │ • Registry │ │ • Anthropic │ │
│ │ • Wizard │ │ • Executor │ │ • Selection │ │ • OpenAI │ │
│ │ • Output │ │ • Context │ │ • Loading │ │ • Google │ │
│ │ │ │ │ │ │ │ • Local │ │
│ └─────────────┘ └──────────────┘ └─────────────┘ └─────────────┘ │
│ │
│ ┌─────────────┐ ┌──────────────┐ ┌─────────────┐ ┌─────────────┐ │
│ │ Session │ │ Config │ │ MCP │ │ Services │ │
│ │ │ │ │ │ │ │ │ │
│ │ • State │ │ • Loader │ │ • Server │ │ • Logging │ │
│ │ • Context │ │ • Schema │ │ • Tools │ │ • Cleanup │ │
│ │ • History │ │ • Providers │ │ • Prompts │ │ • Utils │ │
│ └─────────────┘ └──────────────┘ └─────────────┘ └─────────────┘ │
│ │
└─────────────────────────────────────────────────────────────────────────┘
Key Design Principles
| Principle | Implementation |
|---|---|
| Modularity | Loosely coupled components with clear interfaces |
| Extensibility | Plugin architecture for agents, commands, providers |
| Testability | Comprehensive test suites (unit, integration, e2e) |
| Observability | Structured logging and session tracking |
| Resilience | Graceful fallbacks and error recovery |
📋 Commands
Complete Command Reference
| Command | Agent | Description |
|---|---|---|
refine-specs |
@product-manager | Collaboratively refine specifications |
create-prd |
@product-manager | Generate Product Requirements Document |
create-backlog |
@product-manager | Decompose PRD into tasks |
fetch-task |
@product-manager | Retrieve next priority task |
refine-task |
@product-manager | Clarify task requirements |
gather-knowledge |
@lead | Analyse codebase context |
plan |
@lead | Create implementation plan |
review-plan |
@lead | Validate plan quality |
implement |
Dynamic | Execute code changes |
assert |
@asserter | Validate implementation |
test |
@qa | Execute test suites |
review-code |
@lead | Code quality review |
review-functional |
@lead | Functional review |
commit |
@lead | Create conventional commits |
create-pr |
@lead | Generate pull request |
feedback |
@product-manager | Capture outcomes |
Command Categories
┌─────────────────────┐ ┌─────────────────────┐ ┌─────────────────────┐
│ Planning │ │ Implementation │ │ Delivery │
├─────────────────────┤ ├─────────────────────┤ ├─────────────────────┤
│ • refine-specs │ │ • implement │ │ • commit │
│ • create-prd │ │ • assert │ │ • create-pr │
│ • plan │ │ • test │ │ • feedback │
│ • review-plan │ │ • review-code │ │ │
│ • gather-knowledge │ │ • review-functional │ │ │
└─────────────────────┘ └─────────────────────┘ └─────────────────────┘
📚 Documentation
👤 User GuideGetting started, workflows, |
💻 Developer GuideArchitecture, codebase, |
🏛️ ArchitectureSystem design |
Documentation Structure
documentation/
├── README.md # Documentation entry point
├── user-guide/ # For users
│ ├── quick-start.md # 5-minute getting started
│ ├── workflows.md # Common patterns
│ └── commands.md # Command reference
├── developer-guide/ # For developers
│ ├── setup.md # Development environment
│ ├── codebase.md # Code structure
│ └── contributing.md # How to contribute
├── architecture/ # For architects
│ ├── system-architecture.md # C4 diagrams
│ ├── components.md # Component design
│ └── data-flow.md # Data flow patterns
└── adr/ # Decision records
├── 001-multi-agent-architecture.md
├── ...
├── 008-pretooluse-cli-enforcement.md
└── 009-supply-chain-hardening.md
🎯 Use Cases
New Feature Development
valora refine-specs "User authentication with OAuth"
valora create-prd
valora create-backlog
valora fetch-task && valora plan
valora implement
valora review-code && valora commit
valora create-pr
Bug Fix Workflow
valora plan "Fix: Login timeout issue"
valora implement
valora test --type=all
valora commit --scope=fix
Code Review
valora review-code --focus=security
valora review-functional --check-a11y=true
🔧 Project Structure
valora/ # npm package root
├── bin/ # CLI entry points
│ ├── valora.js # Main CLI
│ └── mcp.js # MCP server
├── src/ # TypeScript source
│ ├── ast/ # AST-based code intelligence (tree-sitter parsing, symbol index)
│ ├── cli/ # Command-line interface
│ ├── config/ # Configuration management
│ ├── executor/ # Pipeline execution
│ ├── llm/ # LLM provider integrations
│ ├── lsp/ # LSP integration (language server protocol client)
│ ├── mcp/ # MCP server implementation
│ ├── security/ # Agentic AI security (credential, command, injection guards)
│ ├── session/ # Session management
│ │ └── worktree-stats-tracker.ts # Worktree usage statistics
│ ├── ui/ # Terminal UI (dashboard, panels)
│ ├── utils/ # Utilities & path resolution
│ └── ...
├── data/ # Built-in resources (shipped with package)
│ ├── agents/ # Agent definitions (11 agents)
│ ├── commands/ # Command specifications (24 commands)
│ ├── prompts/ # Structured prompts by phase
│ ├── templates/ # Document templates
│ ├── hooks/ # Hook scripts
│ ├── config.default.json # Default configuration
│ ├── hooks.default.json # Default hooks config
│ └── external-mcp.default.json # External MCP server registry
├── dist/ # Compiled output (gitignored)
├── tests/ # Test suites
├── documentation/ # Comprehensive docs
└── package.json
Project-Level Overrides (.valora/)
When installed in a project, VALORA supports a .valora/ directory for local overrides:
.valora/ # Project-specific configuration
├── config.json # Project settings (overrides defaults)
├── agents/ # Custom/override agent definitions
├── commands/ # Custom/override command specs
├── prompts/ # Custom/override prompts
├── templates/ # Custom/override templates
├── sessions/ # Session state (gitignored)
├── logs/ # Execution logs (gitignored)
├── index/ # Codebase symbol index (gitignored)
└── cache/ # Cache data (gitignored)
Resources in .valora/ take precedence over built-in data/ resources.
🌟 Why VALORA?
Traditional Development
|
With AI Orchestration
|
Innovation Highlights
| Innovation | Impact |
|---|---|
| Multi-Agent Orchestration | Specialised agents produce expert-level output |
| Three-Tier Execution | Flexibility from free to fully automated |
| Session Persistence | Context flows naturally between commands |
| Dynamic Agent Selection | Right expert for every task |
| Quality Gates | Multiple checkpoints prevent technical debt |
🛠️ Technology Stack
| Category | Technologies |
|---|---|
| Runtime | Node.js 18+, TypeScript 5.x |
| Package Manager | pnpm 10.x |
| Build | tsc, tsc-alias |
| Testing | Vitest, Playwright |
| LLM SDKs | @anthropic-ai/sdk, openai, @google/generative-ai |
| CLI UI | Ink (React), Chalk, Commander |
| Validation | Zod |
| Code Intelligence | web-tree-sitter |
| MCP | @modelcontextprotocol/sdk |
📄 Licence
MIT © Damien TIVELET
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