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Assess portfolio risk using npx neural-trader — VaR, CVaR, Sharpe, position sizing, circuit breaker status
| name | trader-risk |
| description | Assess portfolio risk using npx neural-trader — VaR, CVaR, Sharpe, position sizing, circuit breaker status |
| allowed-tools | Bash Read mcp__claude-flow__memory_store mcp__claude-flow__memory_search |
| argument-hint | [--symbol TICKER] [--portfolio NAME] |
Assess portfolio and position risk using neural-trader's risk engine.
Steps:
npm ls neural-trader 2>/dev/null || npm install --ignore-scripts neural-trader# Single position
npx neural-trader --risk assess --symbol TICKER
npx neural-trader --var --symbol TICKER --investment 10000
# Portfolio-wide
npx neural-trader --risk assess --portfolio NAME
npx neural-trader --correlation --portfolio NAME --flag-threshold 0.8
npx neural-trader --risk-tolerance 0.02 --symbol TICKER
npx neural-trader --position-sizing kelly --symbol TICKER
mcp__claude-flow__memory_store({ key: "risk-TICKER-DATE", value: "RISK_METRICS", namespace: "trading-risk" })Spawn nested sub-agents (agents that spawn sub-agents, up to depth=5) via Claude Code's native Task tool — for context-managed deep delegation
Author a workflow — either an MCP workflow template (persisted, lifecycle) or a native .claude/workflows/*.js orchestration script (agent/parallel/pipeline fan-out)
Run a workflow — drive an MCP workflow lifecycle (execute/pause/resume/cancel) or invoke + resume a native .claude/workflows/*.js orchestration via the Workflow tool
Side-by-side comparison of ruflo vs HAL vs other GAIA harnesses — capability gaps, design decisions, and improvement roadmap
Diagnose why a GAIA question failed — extract trace, classify failure mode, and propose a fix
Walk through a complete GAIA benchmark→submit flow — from key resolution through HAL-compatible package generation