LQF_Machine_Learning_E…
LQF Machine Learning Expert Guide - Routed skill for ML/Statistical Modeling with Critical Discussion Mode. Triggers on: machine learning, modeling,…
Benchmark indicator performance with BenchmarkDotNet. Use for Series/Buffer/Stream benchmarks, regression detection, and optimization patterns. Target 1.5x Series for StreamHub, 1.2x for BufferList.
$ npx -y skills add foryourhealth111-pixel/Vibe-Skills --skill performance-testing --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/performance-testingContext preview
The summary Claude sees to decide when to auto-load this skill.
Benchmark indicator performance with BenchmarkDotNet. Use for Series/Buffer/Stream benchmarks, regression detection, and optimization patterns. Target 1.5x Series for StreamHub, 1.2x for BufferList.
name: performance-testing description: Benchmark indicator performance with BenchmarkDotNet. Use for Series/Buffer/Stream benchmarks, regression detection, and optimization patterns. Target 1.5x Series for StreamHub, 1.2x for BufferList.
cd tools/performance # Run all benchmarks (~15-20 minutes) dotnet run -c Release # Run specific category dotnet run -c Release --filter *StreamIndicators* dotnet run -c Release --filter *BufferIndicators* dotnet run -c Release --filter *SeriesIndicators* # Run specific indicator dotnet run -c Release --filter *.EmaHub
[Benchmark] public void ToMyIndicator() => quotes.ToMyIndicator(14);
[Benchmark] public object MyIndicatorHub() => quoteHub.ToMyIndicatorHub(14).Results;
[Benchmark]
public MyIndicatorList MyIndicatorList() => new(14) { quotes };[Benchmark] public IReadOnlyList<MyResult> MyIndicatorSeries() => quotes.ToMyIndicator(14); [Benchmark] public IReadOnlyList<MyResult> MyIndicatorBuffer() => quotes.ToMyIndicatorList(14); [Benchmark] public IReadOnlyList<MyResult> MyIndicatorStream() => quoteHub.ToMyIndicator(14).Results;
**Note**: These are optimization goals for future v3.1+ effort. Current implementations vary—see `PERFORMANCE_ANALYSIS.md` for actual measured performance. Some indicator families (e.g., EMA) have inherent framework overhead due to simple operation costs.
| Style | Target vs Series | Use Case | | ----- | ---------------- | -------- | | Series | Baseline | Batch processing | | BufferList | ≤ 1.2x | Incremental data | | StreamHub | ≤ 1.5x | Real-time feeds |
**Note**: These are optimization targets. Actual execution times vary by indicator complexity and current implementation.
| Complexity | Time | Examples | | ---------- | ---- | -------- | | Fast | < 30μs | SMA, EMA, WMA, RSI | | Medium | 30-60μs | MACD, Bollinger Bands, ATR | | Complex | 60-100μs | HMA, ADX, Stochastic | | Advanced | 100-200μs+ | Ichimoku, Hurst |
# Auto-detect baseline and results pwsh detect-regressions.ps1 # Custom threshold (default 10%) pwsh detect-regressions.ps1 -ThresholdPercent 15
Exit codes:
cp BenchmarkDotNet.Artifacts/results/Performance.*-report-full.json \ baselines/baseline-v3.0.0.json
See `references/benchmark-patterns.md` for detailed patterns.
--- Last updated: December 31, 2025
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Repo: foryourhealth111-pixel/Vibe-Skills
LQF Machine Learning Expert Guide - Routed skill for ML/Statistical Modeling with Critical Discussion Mode. Triggers on: machine learning, modeling,…
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