An ambient, proactive agent that handles low-risk work automatically
and briefs you only when your judgment is needed.
中文 · Agent Spec · Dashboard
Picture yourself playing a grand strategy game — Hearts of Iron or Civilization. You don't want to manage "the 1st Corps is missing a rifle." You want to set the strategy and let the system adapt and execute based on the situation.
Your real work life is the same:
80% of your tasks are low-risk, automatable noise. Your attention should be reserved for the 20% that truly require your judgment.
Steward is your digital chief of staff — it silently monitors emails, GitHub, calendars, chat, and more, proactively identifies and advances your to-dos. Low-risk tasks get done automatically. You're only interrupted for decisions that matter.
| Feature | Description |
|---|---|
| 🔇 Ambient | Runs 24/7 in the background, zero popups by default |
| 🧠 Multi-Source Perception | GitHub, email, calendar, chat, screen — all first-class signal sources |
| ⚡ Autonomous Execution | Low-risk tasks auto-completed with full audit trail and rollback capability |
| 🛡️ Policy Gate | High-risk / irreversible actions require explicit human approval — no override possible |
| 📋 Periodic Briefs | Every 4 hours: natural language summary of "what was done, what's pending, what needs your call" |
| 🔌 Pluggable Connectors | Slack, Gmail, Google Calendar, MCP — unified connector protocol |
| 🧩 Conflict Arbiter | When multiple plans compete for the same resource: auto merge / serialize / escalate |
One command. That's it.
git clone https://github.com/user/Steward.git
cd Steward
make startAn interactive wizard walks you through setup:
╔══════════════════════════════════════╗
║ 🤖 Steward Quick Start ║
╚══════════════════════════════════════╝
✅ Python: Python 3.14.2
✅ Virtual environment created
✅ Dependencies installed
📋 Configure LLM API (required)
Select your LLM provider:
1) OpenAI 2) DeepSeek 3) NVIDIA NIM
4) GLM 5) Moonshot 6) Custom URL
Enter API Key: ▎
🚀 All set! Starting Steward...
Dashboard: http://127.0.0.1:8000/dashboard
Just one API Key — no Docker, no manual config editing.
💡 Power users: For PostgreSQL, set
STEWARD_DATABASE_URLand rundocker compose up -d && make upgrade.
Signal Sources (GitHub / Email / Calendar / Screen / MCP)
│
▼
┌─────────────┐
│ Perception │ ← Webhooks / Polling / Screen Sensor
└──────┬──────┘
│
▼
┌─────────────┐
│ Context Space│ ← Cross-source aggregation & entity resolution
└──────┬──────┘
│
▼
┌─────────────┐
│ Policy Gate │ ← Risk assessment, confidence, interruption budget
└──────┬──────┘
│
┌────┴────┐
▼ ▼
Auto-exec Ask User
│ │
▼ ▼
┌─────────────┐
│ Brief & Audit│ ← NL summaries, full decision trace
└─────────────┘
| Layer | Technology |
|---|---|
| Language | Python 3.14 + asyncio |
| API | FastAPI + Uvicorn |
| Data | SQLite (default) / PostgreSQL + SQLAlchemy + Alembic |
| Scheduling | APScheduler (event-driven first, polling as fallback) |
| Models | Any OpenAI-compatible API |
| Observability | structlog + OpenTelemetry + Prometheus |
steward/
├── api/ # FastAPI routes (REST + Webhooks)
├── core/ # Config, logging, model layer
├── domain/ # Enums, schemas, domain models
├── infra/ # Database, migrations
├── connectors/ # GitHub / Email / Calendar / MCP connectors
├── services/ # Core logic (policy gate, briefs, conflict arbiter)
├── runtime/ # Scheduler, state machine
├── macos/ # macOS menu bar & screen sensor
└── ui/ # Dashboard frontend
- agent.md: The full design specification (800+ lines) — first-principles derivation of Context Space, Policy Gate, Conflict Arbiter, State Machine, personalized learning, and every other mechanism.
Issues and PRs welcome. Please read agent.md first to understand the design philosophy.
make lint # Code linting
make test # Run tests
make format # Code formatting