TradeGuard

**TradeGuard** is a human-in-the-loop options-trading agent built for the Options Alpha Agents track. Rather than competing on autonomous complexity, TradeGuard focuses on the harder problem: making AI-assisted trading safe, auditable, and controllable. The workflow is deliberately strict. A Go backend reads real market context — quotes, news, and option chains — through a read-only MCP connection. An LLM (Fireworks AI, Kimi K3) then proposes at most one options contract per symbol per cycle: a long call or put to open a new position, sized within a hard position-size cap. Each proposal includes plain-language bull and bear reasoning. **Nothing executes automatically.** A human reviews the complete proposal in a Flutter app and chooses **Approve** or **Deny**. Only after approval does a separate Go executor, using the Alpaca Trading API directly and never through the LLM, place the paper order. Safety is enforced through independent layers. The LLM has no order-placement tools, while a denylist blocks tools named “order” or “delete.” Position-size limits are enforced both in the app and again by the executor. A kill switch is checked by both the agent and executor before action. Contract proposals are also validated against real, pre-filtered candidates before storage, preventing hallucinated symbols from reaching execution. Every outcome — approved, denied, executed, over-cap, or broker-rejected — is recorded in a permanent audit trail with its reason. The Flutter app provides three realtime views: **Queue, Portfolio, and Audit**, all synced live through PocketBase. The demo is fully end-to-end: a real MCP connection to an Alpaca paper account, live market data and option chains, LLM-generated reasoning, human approvals and denials, real paper orders, and complete audit logging.