Comparison with adjacent projects¶
TraderHarness is environment and evidence infrastructure. It can host different agent architectures without prescribing an investment methodology.
| Project | Primary responsibility | Native decision unit | What integration still needs |
|---|---|---|---|
| TraderHarness | Historically valid market, execution, portfolio, evaluation, replay, trajectories | Autonomous agent, isolated comparison, or single-executor committee | An agent card or external framework |
| TradingAgents | Multi-role analysts, debate, risk, and trader workflow | Prescribed role graph | A strict benchmark market and order contract |
| StockBench | Standardized stock-reasoning benchmark tasks | Benchmark task or prediction | Persistent portfolio and autonomous tool loop |
| Qlib | Quant data, models, experiments, and strategies | ML model or code strategy | LLM-native tools and language-output contamination controls |
| Backtrader / vn.py | Strategy execution and trading infrastructure | Code strategy | Autonomous LLM research loop, masking, and trajectory contract |
Independent agents versus a committee¶
traderharness compare is a race: every agent has its own cash, positions, memory, and portfolio. All agents share a market clock and are scored independently.
A committee is one competitor: read-only advisors may research, but exactly one trader owns the order tool and one portfolio. See multi-role committees.
Integrate your framework¶
An external LangGraph, TradingAgents, or custom orchestrator should implement the public agent protocol and return a final decision. Market reads and orders still pass through TraderHarness, inheriting the same clock, masks, progressive intraday visibility, and matching rules.