💡 Summary
OpenProse is a programming language designed for orchestrating AI agents within a session.
🎯 Target Audience
🤖 AI Roast: “Powerful, but the setup might scare off the impatient.”
Risk: Medium. Review: shell/CLI command execution; outbound network access (SSRF, data egress); filesystem read/write scope and path traversal. Run with least privilege and audit before enabling in production.
# Research and write workflow agent researcher: model: sonnet skills: ["web-search"] agent writer: model: opus parallel: research = session: researcher prompt: "Research quantum computing breakthroughs" competitive = session: researcher prompt: "Analyze competitor landscape" loop until **the draft meets publication standards** (max: 3): session: writer prompt: "Write and refine the article" context: { research, competitive }
Install
Claude Code
claude plugin marketplace add openprose/prose claude plugin install open-prose@prose
Then launch Claude Code and try:
"run example prose program and teach me how it works"
OpenCode
git clone https://github.com/openprose/prose.git ~/.config/opencode/skill/open-prose
Then launch OpenCode and try:
"run example prose program and teach me how it works"
Amp
git clone https://github.com/openprose/prose.git ~/.config/agents/skills/open-prose
Then launch Amp and try:
"run example prose program and teach me how it works"
By installing, you agree to the Privacy Policy and Terms of Service.
The Intelligent Inversion of Control
Traditional orchestration requires explicit coordination code. OpenProse inverts this—you declare agents and control flow, and an AI session wires them up. The session is the IoC container.
1. The Session as Runtime
Other frameworks orchestrate agents from outside. OpenProse runs inside the agent session—the session itself is both interpreter and runtime. It doesn't just match names; it understands context and intent.
2. The Fourth Wall (**...**)
When you need AI judgment instead of strict execution, break out of structure:
loop until **the code is production ready**: session "Review and improve"
The **...** syntax lets you speak directly to the OpenProse VM. It evaluates this semantically—deciding what "production ready" means based on context.
3. Open Standard, Zero Lock-in
OpenProse runs on any Prose Complete system—a model + harness combination capable of inducing the VM. Currently: Claude Code + Opus, OpenCode + Opus, Amp + Opus. It's not a library you're locked into—it's a language specification.
Switch platforms anytime. Your .prose files work everywhere.
4. Structure + Flexibility
Why not just plain English? You can—that's what **...** is for. But complex workflows need unambiguous structure for control flow. The AI shouldn't have to guess whether you want sequential or parallel execution.
Why not rigid frameworks? They're inflexible. OpenProse gives you structure where it matters (control flow, agent definitions) and natural language where you want flexibility (conditions, context passing).
Update
Claude Code
Enable auto-updates (recommended):
/plugin → Marketplaces → prose → Enable auto-update
Or update manually:
claude plugin update open-prose@prose
OpenCode
cd ~/.config/opencode/skill/open-prose && git pull
Amp
cd ~/.config/agents/skills/open-prose && git pull
Language Features
| Feature | Example |
|---------|---------|
| Agents | agent researcher: model: sonnet |
| Sessions | session "prompt" or session: agent |
| Persistent Agents | agent captain: persist: true / resume: captain |
| Parallel | parallel: blocks with join strategies |
| Variables | let x = session "..." |
| Context | context: [a, b] or context: { a, b } |
| Fixed Loops | repeat 3: and for item in items: |
| Unbounded Loops | loop until **condition**: |
| Error Handling | try/catch/finally, retry |
| Pipelines | items \| map: session "..." |
| Conditionals | if **condition**: / choice **criteria**: |
See the Language Reference for complete documentation.
Examples
The examples/ directory contains 37 example programs:
| Range | Category | |-------|----------| | 01-08 | Basics (hello world, research, code review, debugging) | | 09-12 | Agents and skills | | 13-15 | Variables and composition | | 16-19 | Parallel execution | | 20-21 | Loops and pipelines | | 22-23 | Error handling | | 24-27 | Advanced (choice, conditionals, blocks, interpolation) | | 28 | Gas Town (multi-agent orchestration) | | 29-31 | Captain's chair pattern (persistent orchestrator) | | 33-36 | Production workflows (PR auto-fix, content pipeline, feature factory, bug hunter) | | 37 | The Forge (build a browser from scratch) |
Start with 01-hello-world.prose or try 37-the-forge.prose to watch AI build a web browser.
How It Works
The OpenProse VM
LLMs are simulators. When given a detailed system description, they don't just describe it—they simulate it. The OpenProse specification (prose.md) describes a virtual machine with enough fidelity that a Prose Complete system reading it becomes that VM.
This isn't metaphor: each session triggers a real subagent, outputs are real artifacts, and state persists in conversation history or files. Simulation with sufficient fidelity is implementation.
The VM maps traditional components to emergent structures:
| Aspect | Behavior |
|--------|----------|
| Execution order | Strict — follows program exactly |
| Session creation | Strict — creates what program specifies |
| Parallel coordination | Strict — executes as specified |
| Context passing | Intelligent — summarizes/transforms as needed |
| Condition evaluation | Intelligent — interprets **...** semantically |
| Completion detection | Intelligent — determines when "done" |
Documentation Files
| File | Purpose | When to Load |
|------|---------|--------------|
| prose.md | VM / Interpreter | Load to run programs |
| compiler.md | Compiler / Validator | Only when compiling or validating |
| state/filesystem.md | File-based state (default) | Load with VM |
| state/in-context.md | In-context state | For simple programs (<30 statements) |
| state/sqlite.md | SQLite state (experimental) | On request with --state=sqlite |
| state/postgres.md | PostgreSQL state (experimental) | On request with --state=postgres |
Experimental: SQLite State
Run with --state=sqlite for queryable, transaction-safe state management. Requires sqlite3 CLI:
| Platform | Availability |
|----------|--------------|
| macOS | Pre-installed |
| Linux | apt install sqlite3 or equivalent |
| Windows | winget install SQLite.SQLite |
Experimental: PostgreSQL State
Run with --state=postgres for true concurrent writes, network access, and external system integration.
⚠️ Bring Your Own Database: You are responsible for providing and managing your PostgreSQL instance. OpenProse does not provision databases for you.
⚠️ Security Warning: Database credentials in OPENPROSE_POSTGRES_URL are passed to subagent sessions and will be visible in agent context/logs. Treat these credentials as non-sensitive. Use:
- A dedicated database for OpenProse (not your production DB)
- A user with minimal privileges (just the
openproseschema) - Credentials you're comfortable being logged
Setup:
| Platform | Setup |
|----------|-------|
| macOS | brew install postgresql@16 + brew services start postgresql@16 |
| Linux | apt install postgresql |
| Windows | PostgreSQL installer or Docker |
| Cloud | Neon, Supabase, Railway, etc. |
| Docker | docker run -d --name prose-pg -e POSTGRES_DB=prose -e POSTGRES_HOST_AUTH_METHOD=trust -p 5432:5432 postgres:16 |
Configure connection:
mkdir -p .prose echo "OPENPROSE_POSTGRES_URL=postgresql://user:pass@localhost:5432/prose" >> .prose/.env
PostgreSQL state is for power users who need concurrent parallel writes or external dashboard integration.
FAQ
Why not LangChain/CrewAI/AutoGen? Those are orchestration libraries—they coordinate agents from outside. OpenProse runs inside the agent session—the session itself is the IoC container. Zero external dependencies, portable across any AI assistant.
Why not just plain English?
You can use **...** for that. But complex workflows need unambiguous structure for control flow—the AI shouldn't guess whether you want sequential or parallel execution.
What's "intelligent IoC"? Traditional IoC containers (Spring, Guice) wire up dependencies from configuration. OpenProse's container is an AI session that wires up agents using understanding. It doesn't just match names—it understands context, intent, and can make intelligent decisions about execution.
Beta & Legal
Beta Status
OpenProse is in beta. This means:
- Telemetry is on by default — We collect anonymous usage data to improve the project. See our Privacy Policy for details and how to opt out.
- Expect bugs — The software may behave unexpectedly. Please report issues at github.com/openprose/prose/issues.
- Not for production — Do not use OpenProse for critical or production workflows yet.
- We want feedback — Your input shapes the project. Open issues, suggest features, report problems. See CONTRIBUTING.md for guidelines.
Your Responsibility
You are responsible for all actions performed by AI agents you spawn through OpenProse. Review your .prose programs be
Pros
- Flexible orchestration of AI agents
- Supports complex workflows with clear structure
- Cross-platform compatibility
- Innovative use of natural language for control flow
Cons
- Still in beta, may have bugs
- Requires understanding of new syntax
- Limited documentation on advanced features
- Potential security risks with database integration
Related Skills
pytorch
S“It's the Swiss Army knife of deep learning, but good luck figuring out which of the 47 installation methods is the one that won't break your system.”
agno
S“It promises to be the Kubernetes for agents, but let's see if developers have the patience to learn yet another orchestration layer.”
nuxt-skills
S“It's essentially a well-organized cheat sheet that turns your AI assistant into a Nuxt framework parrot.”
Disclaimer: This content is sourced from GitHub open source projects for display and rating purposes only.
Copyright belongs to the original author openprose.
