# Generic AI Trading Agent Interface
# Upstream: TauricResearch/TradingAgents#264
# Branch: contrib/024-generic-agent-interface (based on source/main)
# Push: git push upstream contrib/024-generic-agent-interface
# PR: claytonbrown/TradingAgents → TauricResearch/TradingAgents
# Priority: P1

## Problem
No standardized input/output contract for agents. Hard to swap, compose, or benchmark agents.

## Tasks
- [x] 1. Define AgentInput schema: ticker, date, context (market data, news, fundamentals)
- [x] 2. Define AgentOutput schema: rating (5-tier), confidence, price_targets, thesis, risk_factors
- [x] 3. Create BaseAgent abstract class with analyze(input) -> output contract
- [ ] 4. Refactor existing agents (fundamentals, sentiment, news, technical) to implement BaseAgent
- [ ] 5. Create AgentRegistry for pluggable agent discovery
- [ ] 6. Add agent benchmarking: compare outputs across different LLM backends
- [ ] 7. Document interface for third-party agent contributions