by olaxbt · Codex Skill · ★ 1.8k
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AI Market Maker: Agentic Trading System for Crypto Hedge Funds AI-Market-Maker is an open-source, hedge-fund-style trading stack for crypto. It combines specialist AI trading agents (acting as trading desks), a LangGraph orchestration layer, a hard Risk Guard veto before any execution, and quant-grade discipline including centralized policy, benchmarks against buy-and-hold, and full traceability. Designed to feel like a small professional trading firm — not just another bot. Key Features Multi-agent workflow with clear desk responsibilities Strict Risk Guard that can veto any trade Quant-style backtesting with built-in benchmarks (excess return vs buy-and-hold) Unified agent interface + governance layer OpenClaw-ready packaging ( + ) Paper trading on Binance Testnet + rich local backtester Modern web dashboard for telemetry and traces Clean configuration (JSON policy + env for secrets only) Goals Current (Trading Mode) Fetch real-time data, generate signals through specialist agents, run portfolio logic, apply Risk Guard veto, and execute on Binance Testnet.
| Stars | 1,775 |
| Forks | 246 |
| Language | Python |
| Category | Codex Skill |
| License | AGPL-3.0 |
| Quality Score | 73.5634023010828/100 |
| Last Updated | 2026-06-21 |
| Created | 2025-05-22 |
| Platforms | python |
| Est. Tokens | ~15k |
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Explore other popular codex skill tools:
ai-market-maker is Agentic AI Hedge Fund OS (AIMM). It is categorized as a Codex Skill with 1.8k GitHub stars.
ai-market-maker is primarily written in Python. It covers topics such as agentic-trading, claw, crypto.
You can find installation instructions and usage details in the ai-market-maker GitHub repository at github.com/olaxbt/ai-market-maker. The project has 1.8k stars and 246 forks, indicating an active community.
ai-market-maker is released under the AGPL-3.0 license, making it free to use and modify according to the license terms.
The top alternatives to ai-market-maker on Agent Skills Hub include openakita, hope-agent, TradingAgents-AShare. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.