trade-analyze

Multi-agent stock analysis generates a unified Trade Score by coordinating five parallel AI agents that evaluate technical, fundamental, sentiment, risk, and thesis perspectives, synthesizing these dimensions into a single composite score for investment decisions.

To run a multi-dimensional stock analysis on a specific ticker, invoke the command /trade analyze <TICKER> to trigger the full multi-agent workflow, which outputs a composite score, an investment narrative, and recommended next steps.

Yes, you can use this multi-agent stock analysis for portfolio-level screening. Portfolio managers can quickly screen multiple tickers to identify which names warrant deeper qualitative and quantitative scrutiny before committing capital.

The parallel AI agents cover five investment dimensions: technical analysis, fundamental analysis, market sentiment, risk assessment, and investment thesis evaluation, ensuring a cross-dimension evaluation for ticker-level research.

The best way to evaluate stock risk and thesis before investing is using a coordinated multi-agent workflow that analyzes risk and thesis perspectives in parallel alongside technical, fundamental, and sentiment data to produce an interpretable investment verdict.

The standardized output of this stock analysis workflow includes a composite Trade Score, a readable investment narrative explaining the cross-dimension evaluation, and recommended next steps for further deep-dives into the ticker.