tech-stack-evaluation
Use when "evaluating technology", "choosing frameworks", "stack comparison", "technology decisions", or asking about "React vs Vue", "PostgreSQL vs MySQL", "AWS vs GCP", "build vs buy"
video-downloader
Use when "downloading videos", "saving YouTube videos", "converting to MP3", "video quality", or asking about "yt-dlp", "video formats", "audio extraction"
agent-evaluation
Use when evaluating agent performance, building test frameworks, measuring quality, or asking about "agent evaluation", "LLM-as-judge", "agent testing", "quality metrics", "evaluation rubrics", "agent benchmarks"
codex
Use when "codex", "use gpt", "gpt-5", "openai codex", "let openai", "full-auto", "autonomous code generation"
context-compression
Use when compressing agent context, implementing conversation summarization, reducing token usage in long sessions, or asking about "context compression", "conversation history", "token optimization", "context limits", "summarization strategies"
context-degradation
Use when diagnosing agent failures, debugging lost-in-middle issues, understanding context poisoning, or asking about "context degradation", "lost in middle", "context poisoning", "attention patterns", "context clash", "agent performance drops"
context-optimization
Use when optimizing agent context, reducing token costs, implementing KV-cache optimization, or asking about "context optimization", "token reduction", "context limits", "observation masking", "context budgeting", "context partitioning"
crewai-agents
Use when "CrewAI", "multi-agent systems", "agent orchestration", "AI crews", or asking about "autonomous agents", "agent collaboration", "role-based agents", "agent workflows", "AI team coordination"
dispatching-parallel-agents
Use when facing 2+ independent tasks that can be worked on without shared state or sequential dependencies
dspy-prompting
Use when "DSPy", "declarative prompting", "automatic prompt optimization", "Stanford NLP", or asking about "optimizing prompts", "prompt compilation", "modular LLM programming", "chain of thought", "few-shot learning"
executing-plans
Use when you have a written implementation plan to execute in a separate session with review checkpoints
langchain-agents
Use when "LangChain", "LLM chains", "ReAct agents", "tool calling", or asking about "RAG pipelines", "conversation memory", "document QA", "agent tools", "LangSmith"
mcp-development
Use when building "MCP server", "Model Context Protocol", creating "Claude tools", "MCP tools", or asking about "FastMCP", "MCP SDK", "tool development for LLMs", "external API integration for Claude"
memory-systems
Use when implementing agent memory, persisting state across sessions, building knowledge graphs, tracking entities, or asking about "agent memory", "knowledge graph", "entity memory", "vector stores", "temporal knowledge", "cross-session persistence"
multi-agent-patterns
Use when designing multi-agent systems, implementing supervisor patterns, coordinating multiple agents, or asking about "multi-agent", "supervisor pattern", "swarm", "agent handoffs", "orchestration", "parallel agents"
nanobanana
Use when "nanobanana", "generate image", "create image", "edit image", "AI drawing", "Gemini image", "image generation"
planning-with-files
This skill should be used when starting complex multi-step tasks, research projects, or any task requiring >5 tool calls. Implements Manus-style file-based planning with task_plan.md, findings.md, and progress.md.
plugin-development
Use when creating Claude Code plugins, writing skills, building commands, developing agents, or asking about "plugin development", "create skill", "write command", "build agent", "SKILL.md", "plugin structure", "progressive disclosure"
prompt-engineering
Use when "writing prompts", "prompt optimization", "few-shot learning", "chain of thought", or asking about "RAG systems", "agent workflows", "LLM integration", "prompt templates"
subagent-driven-development
Use when executing implementation plans with independent tasks in the current session
syncing-submodules
Use when running /ltk:sync-submodules, updating submodules, or needing to "sync", "merge", "adapt", "learn from" other Claude Code plugins or repos
tool-design
Use when designing agent tools, creating tool descriptions, implementing MCP tools, or asking about "tool design", "agent tools", "tool descriptions", "MCP", "function calling", "tool consolidation"
using-ltk
Use when starting any conversation - establishes how to find and use skills, requiring Skill tool invocation before ANY response including clarifying questions
writing-plans
Use when you have a spec or requirements for a multi-step task, before touching code
writing-skills
Use when creating new skills, editing existing skills, or verifying skills work before deployment
dask
Use when "Dask", "parallel computing", "distributed computing", "larger than memory", or asking about "parallel pandas", "parallel numpy", "out-of-core", "multi-file processing", "cluster computing", "lazy evaluation dataframe"
data-engineering
Use when "data pipelines", "ETL", "data warehousing", "data lakes", or asking about "Airflow", "Spark", "dbt", "Snowflake", "BigQuery", "data modeling"
data-science
Use when "statistical modeling", "A/B testing", "experiment design", "causal inference", "predictive modeling", or asking about "hypothesis testing", "feature engineering", "data analysis", "pandas", "scikit-learn"
experiment-tracking
Use when "experiment tracking", "MLflow", "Weights & Biases", "wandb", "model registry", "hyperparameter logging", "ML experiments", "training metrics"
geopandas
Use when "GeoPandas", "geospatial", "GIS", "shapefile", "GeoJSON", or asking about "spatial analysis", "coordinate transformation", "spatial join", "choropleth map", "buffer analysis", "geographic data", "map visualization"
huggingface-tokenizers
Use when "tokenizers", "HuggingFace tokenizer", "BPE", "WordPiece", or asking about "train tokenizer", "custom vocabulary", "tokenization", "subword", "fast tokenizer", "encode text"
llm-inference
Use when "LLM inference", "serving LLM", "vLLM", "llama.cpp", "GGUF", "text generation", "model serving", "inference optimization", "KV cache", "continuous batching", "speculative decoding", "local LLM", "CPU inference"
llm-training
Use when "training LLM", "finetuning", "RLHF", "distributed training", "DeepSpeed", "Accelerate", "PyTorch Lightning", "Ray Train", "TRL", "Unsloth", "LoRA training", "flash attention", "gradient checkpointing"
ml-engineering
Use when "deploying ML models", "MLOps", "model serving", "feature stores", "model monitoring", or asking about "PyTorch deployment", "TensorFlow production", "RAG systems", "LLM integration", "ML infrastructure"
modal
Use when "Modal", "serverless GPU", "cloud GPU", "deploy ML model", or asking about "serverless containers", "GPU compute", "batch processing", "scheduled jobs", "autoscaling ML"
multimodal-models
Use when "CLIP", "Whisper", "Stable Diffusion", "SDXL", "speech-to-text", "text-to-image", "image generation", "transcription", "zero-shot classification", "image-text similarity", "inpainting", "ControlNet"
nemo-evaluator
Use when evaluating LLMs, running benchmarks like MMLU/HumanEval/GSM8K, setting up evaluation pipelines, or asking about "NeMo Evaluator", "LLM benchmarking", "model evaluation", "MMLU", "HumanEval", "GSM8K", "benchmark harnesses"
networkx
Use when "NetworkX", "graph analysis", "network analysis", "graph algorithms", "shortest path", "centrality", "PageRank", "community detection", "social network", "knowledge graph"
polars
Use when "Polars", "fast dataframe", "lazy evaluation", "Arrow backend", or asking about "pandas alternative", "parallel dataframe", "large CSV processing", "ETL pipeline", "expression API"
pymc
Use when "PyMC", "Bayesian", "MCMC", "probabilistic programming", or asking about "Bayesian regression", "hierarchical model", "NUTS sampler", "posterior distribution", "prior predictive", "credible intervals", "uncertainty quantification"
rag-frameworks
Use when "RAG", "retrieval augmented generation", "LangChain", "LlamaIndex", "sentence transformers", "embeddings", "document QA", "chatbot with documents", "semantic search"
scientific-computing
Use when "scientific computing", "astronomy", "astropy", "bioinformatics", "biopython", "symbolic math", "sympy", "statistics", "statsmodels", "scientific Python"
scikit-learn
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"
shap
Use when "SHAP", "Shapley values", "feature importance", "model explainability", or asking about "explain predictions", "interpretable ML", "feature attribution", "waterfall plot", "beeswarm plot", "model debugging"
transformers
Use when "HuggingFace Transformers", "pre-trained models", "pipeline API", or asking about "text generation", "text classification", "question answering", "NER", "fine-tuning transformers", "AutoModel", "Trainer API"
vector-databases
Use when "vector database", "embedding storage", "similarity search", "semantic search", "Chroma", "ChromaDB", "FAISS", "Qdrant", "RAG retrieval", "k-NN search", "vector index", "HNSW", "IVF"
visualization
Use when "data visualization", "plotting", "charts", "matplotlib", "plotly", "seaborn", "graphs", "figures", "heatmap", "scatter plot", "bar chart", "interactive plots"
Accessibility
This skill should be used when the user asks about "accessibility", "a11y", "WCAG", "screen readers", "keyboard navigation", "ARIA", "accessible design", "inclusive design", or mentions making apps accessible.
Branding
This skill should be used when the user asks about "branding", "brand identity", "logo design", "color palette", "brand guidelines", "visual identity", "brand voice", "style guide", or mentions brand-related decisions.
canvas-design
Use when "creating posters", "visual art", "design philosophy", "PDF art", "PNG design", or asking about "abstract art", "visual design", "museum-quality graphics"
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