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name: tradeblocks-health-check description: Strategy health check for trading backtests. Analyzes performance metrics, runs stress tests, and surfaces risk indicators. Use when evaluating a strategy's historical performance and stress characteristics.

Strategy Health Check

Surface key performance metrics and stress test results to help understand a strategy's characteristics.

Prerequisites

• TradeBlocks MCP server must be running
• At least one block with trade data loaded

Process

Step 1: Select Strategy

List available blocks and help the user choose what to analyze.

CopyUse list_blocks to show available options.

Ask clarifying questions:

• "Which backtest would you like to analyze?"
• "Do you want to analyze the full portfolio or a specific strategy within it?"

If analyzing a specific strategy, note it for filtering in subsequent steps.

Step 2: Gather Basic Metrics

Run get_statistics for the selected block (with strategy filter if specified).

Present key metrics with context:

Key insight: A strategy can have low win rate but high profit factor if average wins exceed average losses significantly. Neither metric alone tells the full story.

Step 3: Stress Testing

Run run_monte_carlo to project performance under uncertainty.

Key parameters to understand:

• resampleMethod: "trades" resamples individual trade P&L (default)
• includeWorstCase: Injects synthetic worst-case scenarios (default: true)
• worstCasePercentage: How much of simulation is worst-case (default: 5%)

Focus on these outputs:

• 5th percentile outcome: What the data suggests in a bad scenario (1 in 20 chance of worse)
• Probability of profit: How often simulations ended profitable
• Mean max drawdown: Typical drawdown across simulations

Present these as "what the historical data suggests could happen" - not predictions.

Step 4: Risk Metrics

Run complementary risk analysis:

1. Position Sizing via get_position_sizing:

   • Kelly criterion calculation based on win rate and payoff ratio
   • Shows full Kelly, half Kelly (0.5x), and quarter Kelly (0.25x) fractions
   • Note: Kelly assumes independent trades, which may not apply

2. Tail Risk via get_tail_risk (if multiple strategies):

   • Joint tail dependence between strategies
   • Effective factors (how many independent risk sources exist)
   • High values indicate strategies may fail together

Key outputs to surface:

• Kelly percentage (what the formula suggests given historical win rate and payoff)
• Warnings in the output (e.g., "Portfolio Kelly exceeds 25%", "negative Kelly")
• Tail risk level (LOW/MODERATE/HIGH based on average joint tail risk)

Step 5: Summary

Synthesize findings into a clear picture of what the data shows:

Metrics Summary:

• Sharpe Ratio: [value] - [context: >1.0 considered acceptable by many, >2.0 considered excellent]
• Max Drawdown: [value] - [context: <20% relatively low, >40% significant]
• Profit Factor: [value] - [context: >1.5 considered good, >2.0 excellent]
• Kelly: [value] - [context: what historical data suggests; negative means losses > wins]

Stress Test Insights:

• 5th percentile scenario: [value]
• Monte Carlo probability of profit: [value]

What stands out:

• [Highlight any notably strong or weak metrics]
• [Note any warnings from the tools]
• [Mention if multiple strategies show high tail correlation]

Let the user draw their own conclusions about whether this fits their risk tolerance.

Interpretation Reference

For detailed explanations of each metric, see references/metrics.md.

Related Skills

After health check, the user may want to:

• /tradeblocks-wfa - Test if optimized parameters hold up on unseen data
• /tradeblocks-risk - Deep dive into position sizing and tail risk analysis

Notes

• Always use trade-based calculations when filtering by strategy (daily logs represent full portfolio)
• Historical performance doesn't guarantee future results
• Kelly criterion assumes independent trades and known edge - real trading may differ