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Found 149 Skills
Guides structured 4-stage experiment execution with attempt budgets and gate conditions: Stage 1 initial implementation (reproduce baseline), Stage 2 hyperparameter tuning, Stage 3 proposed method validation, Stage 4 ablation study. Integrates with evo-memory (load prior strategies, trigger IVE/ESE) and experiment-craft (5-step diagnostic on failure). Use when: user has a planned experiment, needs to reproduce baselines, organize experiment workflow, or systematically validate a method. Do NOT use for debugging a specific experiment failure (use experiment-craft) or designing which experiments to run (use paper-planning).
Dynamic linking skill for Linux/ELF shared libraries. Use when debugging library loading failures, configuring RPATH vs RUNPATH, understanding soname versioning, using dlopen/dlsym for plugin systems, LD_PRELOAD interposition, or controlling symbol visibility. Activates on queries about shared libraries, dlopen, LD_LIBRARY_PATH, RPATH, soname, LD_PRELOAD, symbol visibility, or "cannot open shared object file" errors.
Implements the Syncfusion WPF Color Palette (SfColorPalette) control for color selection interfaces with swatches. Use this when implementing color picker functionality, color swatches, or color binding in WPF applications. Covers setup, color selection, data binding, swatch navigation, appearance customization, and theming.
Automates the Karpathy LLM Wiki workflow: turns web, GitHub, and YouTube URLs into well-structured, citable, wikilinked pages with automatic linting and sourcing — invoke with /pin-llm-wiki
Train ML models with scikit-learn, PyTorch, TensorFlow. Use for classification/regression, neural networks, hyperparameter tuning, or encountering overfitting, underfitting, convergence issues.
Use when "scikit-learn", "sklearn", "machine learning", "classification", "regression", "clustering", or asking about "train test split", "cross validation", "hyperparameter tuning", "ML pipeline", "random forest", "SVM", "preprocessing"
Design experiment plans with progressive stages — initial implementation, baseline tuning, creative research, and ablation studies. Plan baselines, datasets, hyperparameter sweeps, and evaluation metrics. Use when planning experiments for a research paper.
Implements the Syncfusion WPF ColorPickerPalette control for color selection from themed and standard color palettes. Use this when adding color pickers with predefined palettes, customizing color options, or handling color selection events in WPF applications. Covers setup, color management, appearance customization, and interaction patterns.
Guide implementation of the Syncfusion WinUI Color Palette control (SfColorPalette) for swatch-based color selection in Windows desktop applications. Use this skill when working with theme colors, standard colors, custom color palettes, or the More Colors dialog. Covers color palette setup, theme color support, standard color configurations, UI customization, and best practices.
Guidelines for building RoboCorp RPA automation with Python, emphasizing functional programming, Pydantic validation, and async operations.
LLM Wiki — persistent markdown knowledge base that compounds across sessions (Karpathy model)
Distributed training orchestration across clusters. Scales PyTorch/TensorFlow/HuggingFace from laptop to 1000s of nodes. Built-in hyperparameter tuning with Ray Tune, fault tolerance, elastic scaling. Use when training massive models across multiple machines or running distributed hyperparameter sweeps.