# PCL — Persona Control Language
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║ ██████╗ ██████╗██╗ ║
║ ██╔══██╗██╔════╝██║ The World's First Programming Language ║
║ ██████╔╝██║ ██║ for AI Persona Management ║
║ ██╔═══╝ ██║ ██║ ║
║ ██║ ╚██████╗███████╗ Make AI behavior programmable, portable, ║
║ ╚═╝ ╚═════╝╚══════╝ and predictable. ║
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```
[](LICENSE)
[](CHANGELOG.md)
[](https://www.typescriptlang.org/)
[](SECURITY.md)
[![Tests]()](docs/testing/TESTING_STATUS.md)
[](docs/testing/COVERAGE_ROADMAP.md)
**Standards Compliance**:
[](GOVERNANCE/PCL_SECURITY_MODEL.md)
[](GOVERNANCE/PCL_GOVERNANCE.md)
[](GOVERNANCE/PCL_SECURITY_MODEL.md)
[](SPEC/PCL_SPEC_v1.md)
---
## What is PCL?
**PCL (Persona Control Language)** is a **governance-first programming language** for AI persona management and multi-agent orchestration. Unlike traditional application languages, PCL is designed for **accountability, security, and compliance** in AI systems.
### PCL = Terraform + OpenPolicyAgent + AI Personas
PCL enables enterprises and developers to:
- **Define** personas with explicit capabilities, constraints, and risk classifications (ISO 42001)
- **Govern** AI behavior through auditable policies and access controls (ISO 27001)
- **Orchestrate** complex multi-agent workflows with human oversight
- **Deploy** consistently across Claude, GPT, Gemini, Azure, and open-source LLMs
- **Audit** every action with immutable logs aligned to compliance frameworks
- **Comply** with EU AI Act, GDPR, OWASP LLM Top 10, and Zero Trust principles
---
## Quick Example
```pcl
// Define a security analyst persona
pub persona SEC {
intent: "Identify and mitigate security vulnerabilities"
tone: vigilant
skills {
"OWASP Top 10"
"STRIDE threat modeling"
"Security code review"
}
constraints {
"Always assume breach"
maxResponseTime <= 5s
}
}
// Compose a security review team
pub team SecurityReview {
members: [SEC, AUDIT, ARCHI, CRITIC]
primary: SEC
merge: Debate
quorum: 3/4
}
// Define a code review workflow
pub workflow CodeReview {
steps: DEV -> (ARCHI || SEC) -> CRITIC -> merge(Consensus)
timeout: 60s
fallback: SIMPLIFY
}
```
---
## Installation
```bash
# Clone the repository
git clone https://github.com/personamanagmentlayer/pcl.git
cd pcl
# Install dependencies
npm install
# Build PCL
npm run build
# Verify installation
node dist/cli/index.js --version
```
**[📖 Complete Installation Guide →](docs/INSTALLATION.md)**
---
## Documentation
### Getting Started
- **[Quick Start Guide](docs/QUICK_START.md)** - Get started in 5 minutes
- **[Core Concepts](docs/CORE_CONCEPTS.md)** - Personas, Teams, Workflows, and more
- **[Installation Guide](docs/INSTALLATION.md)** - Complete setup instructions
- **[Features Overview](docs/FEATURES.md)** - All features and capabilities
### For Developers
- **[Getting Started Tutorial](docs/guides/GETTING-STARTED-CURRENT.md)** - Practical working introduction
- **[VS Code Setup](docs/guides/VSCODE-SETUP.md)** - IDE configuration
- **[Testing Guide](docs/testing/TESTING_STATUS.md)** - Test coverage and benchmarks
- **[API Reference](docs/api/)** - Parser, Semantic Analysis, Code Generation
### Specifications & Standards
- **[PCL Specification v1.0](SPEC/PCL_SPEC_v1.md)** - RFC-style formal specification
- **[Governance Framework](GOVERNANCE/PCL_GOVERNANCE.md)** - ISO 38500-aligned governance
- **[Security Model](GOVERNANCE/PCL_SECURITY_MODEL.md)** - ISO 27001/42001 security architecture
- **[Standards Overview](GOVERNANCE/STANDARDS_OVERVIEW.md)** - Complete standards alignment
### Complete Documentation Index
**[📚 Full Documentation →](docs/README.md)**
---
## Key Features
### Production-Ready Testing ✅
- **5,720 total tests** (96.3% pass rate)
- **50.66%+ code coverage** (targeting 90%)
- **153 test files** covering all major modules
- **Comprehensive testing**: LSP, Observability, MCP, Registry, Providers, CLI, Codegen, Parser, E2E
**[📊 Testing Status →](docs/testing/TESTING_STATUS.md)** | **[🗺️ Coverage Roadmap →](docs/testing/COVERAGE_ROADMAP.md)**
### Supported AI Providers (8)
Anthropic Claude • OpenAI GPT • Google Gemini • DeepSeek • Ollama • Azure OpenAI • AWS Bedrock • Mock
**[🤖 Provider Guide →](docs/providers/README.md)**
### Core Capabilities
- ✅ **Language Server Protocol (LSP)** - Full IDE support with IntelliSense, diagnostics, navigation
- ✅ **Skills Ecosystem** - 100% compatible with agentskills.io and Claude Code
- ✅ **Model Context Protocol (MCP)** - Expose personas as standardized AI services
- ✅ **Registry System** - 4 backends (Memory, JSON, SQLite, PostgreSQL)
- ✅ **Observability** - Metrics, SLO tracking, tracing, telemetry, health checks
- ✅ **Code Generation** - Multi-target compilation (TypeScript, Python, JSON, YAML, Markdown)
**[🎯 Complete Features List →](docs/FEATURES.md)**
---
## Production Readiness
**Status:** 🟡 **APPROACHING PRODUCTION READY**
**Production Readiness Score: 78/100** (+33 from January 2026)
- ✅ **Safe for:** Development, prototyping, proof-of-concept, internal tools, beta testing
- 🟡 **Approaching:** Production, customer-facing applications (after final security audit)
- ❌ **Not yet ready for:** High-stakes regulated systems (needs 90% coverage)
**[📈 Production Readiness Report →](docs/PRODUCTION-READINESS.md)**
---
## Roadmap
### Phase 1: Foundation ✅ COMPLETE
- ✅ Core compiler implementation
- ✅ 8 AI provider integrations
- ✅ Registry system with 4 backends
- ✅ 50%+ test coverage baseline
### Phase 2: Ecosystem ✅ COMPLETE
- ✅ Language Server Protocol (LSP)
- ✅ VS Code extension
- ✅ Skills ecosystem integration
- ✅ Model Context Protocol (MCP)
### Phase 3: Scale (Q2 2026)
- 🔄 Advanced merge strategies
- 🔄 Event streaming & observability
- 🔄 90% test coverage
- 🔄 Production security audit
### Phase 4: Maturity (Q4 2026)
- 📅 Visual debugging tools
- 📅 Performance profiling
- 📅 Cloud deployment
- 📅 Marketplace
**[🗺️ Complete Roadmap →](.roadmap/ROADMAP.md)**
---
## Community & Support
- 📖 **[Documentation](docs/README.md)** - Complete guides and API reference
- 🐛 **[GitHub Issues](https://github.com/personamanagmentlayer/pcl/issues)** - Bug reports and feature requests
- 💬 **[Discord](https://discord.gg/pcl-lang)** - Community discussion
- 🐦 **[Twitter](https://twitter.com/pcl_lang)** - Updates and announcements
---
## Contributing
We welcome contributions! See **[CONTRIBUTING.md](CONTRIBUTING.md)** for guidelines.
```bash
# Fork and clone the repository
git clone https://github.com/YOUR_USERNAME/pcl.git
cd pcl
# Install dependencies
npm install
# Run tests
npm test
# Build the project
npm run build
```
**[📋 Contributing Guide →](CONTRIBUTING.md)** | **[📜 Code of Conduct →](CODE_OF_CONDUCT.md)**
---
## License
PCL uses dual licensing to support both software development and documentation sharing:
- **Code** (src/, tests/, scripts/): [Apache 2.0](LICENSE) - Permissive software license with patent grant
- **Documentation** (docs/, SPEC/, GOVERNANCE/): [CC BY 4.0](LICENSE-DOCS) - Creative Commons for specs and guides
- **Trademarks**: IbIFACE - See [Trademark Policy](GOVERNANCE/TRADEMARK_POLICY.md)
This dual licensing approach follows industry best practices (Rust, Kubernetes, OpenAPI) and supports PCL's mission as a governance-first standard for enterprise AI.
For contribution licensing, see [NOTICE](NOTICE).
---
**PCL** — _Making AI behavior programmable, portable, and predictable._
**[Get Started](docs/QUICK_START.md)** • **[Documentation](docs/README.md)** • **[Community](https://discord.gg/pcl-lang)**