python-performance-optimization
wshobsonProfile and optimize Python code using cProfile, memory profilers, and performance best practices. Use when debugging slow Python code, optimizing bottlenecks, or improving application performance.
spark-optimization
wshobsonOptimize Apache Spark jobs with partitioning, caching, shuffle optimization, and memory tuning. Use when improving Spark performance, debugging slow jobs, or scaling data processing pipelines.
optimizing-attention-flash
davila7Optimizes transformer attention with Flash Attention for 2-4x speedup and 10-20x memory reduction. Use when training/running transformers with long sequences (>512 tokens), encountering GPU memory issues with attention, or need faster inference. Supports PyTorch native SDPA, flash-attn library, H100 FP8, and sliding window attention.
hqq-quantization
davila7Half-Quadratic Quantization for LLMs without calibration data. Use when quantizing models to 4/3/2-bit precision without needing calibration datasets, for fast quantization workflows, or when deploying with vLLM or HuggingFace Transformers.
peft-fine-tuning
davila7Parameter-efficient fine-tuning for LLMs using LoRA, QLoRA, and 25+ methods. Use when fine-tuning large models (7B-70B) with limited GPU memory, when you need to train less than 1% of parameters with minimal accuracy loss, or for multi-adapter serving. HuggingFace's official library integrated with transformers ecosystem.
quantizing-models-bitsandbytes
davila7Quantizes LLMs to 8-bit or 4-bit for 50-75% memory reduction with minimal accuracy loss. Use when GPU memory is limited, need to fit larger models, or want faster inference. Supports INT8, NF4, FP4 formats, QLoRA training, and 8-bit optimizers. Works with HuggingFace Transformers.
gptq
davila7Post-training 4-bit quantization for LLMs with minimal accuracy loss. Use for deploying large models (70B, 405B) on consumer GPUs, when you need 4× memory reduction with <2% perplexity degradation, or for faster inference (3-4× speedup) vs FP16. Integrates with transformers and PEFT for QLoRA fine-tuning.
unsloth
davila7Expert guidance for fast fine-tuning with Unsloth - 2-5x faster training, 50-80% less memory, LoRA/QLoRA optimization
awq-quantization
davila7Activation-aware weight quantization for 4-bit LLM compression with 3x speedup and minimal accuracy loss. Use when deploying large models (7B-70B) on limited GPU memory, when you need faster inference than GPTQ with better accuracy preservation, or for instruction-tuned and multimodal models. MLSys 2024 Best Paper Award winner.
spark-optimization
sickn33Optimize Apache Spark jobs with partitioning, caching, shuffle optimization, and memory tuning. Use when improving Spark performance, debugging slow jobs, or scaling data processing pipelines.
python-performance-optimization
sickn33Profile and optimize Python code using cProfile, memory profilers, and performance best practices. Use when debugging slow Python code, optimizing bottlenecks, or improving application performance.
V3 Performance Optimization
ruvnetAchieve aggressive v3 performance targets: 2.49x-7.47x Flash Attention speedup, 150x-12,500x search improvements, 50-75% memory reduction. Comprehensive benchmarking and optimization suite.
AgentDB Performance Optimization
ruvnetOptimize AgentDB performance with quantization (4-32x memory reduction), HNSW indexing (150x faster search), caching, and batch operations. Use when optimizing memory usage, improving search speed, or scaling to millions of vectors.
claude-md-improver
anthropicsAudit and improve CLAUDE.md files in repositories. Use when user asks to check, audit, update, improve, or fix CLAUDE.md files. Scans for all CLAUDE.md files, evaluates quality against templates, outputs quality report, then makes targeted updates. Also use when the user mentions "CLAUDE.md maintenance" or "project memory optimization".
cpp-pro
JeffallanUse when building C++ applications requiring modern C++20/23 features, template metaprogramming, or high-performance systems. Invoke for concepts, ranges, coroutines, SIMD optimization, memory management.
1k-performance
OneKeyHQPerformance optimization for React/React Native — re-renders, memoization, FlashList, memory leaks, and bundle size.
context-engineering
mrgoonieMaster context engineering for AI agent systems. Use when designing agent architectures, debugging context failures, optimizing token usage, implementing memory systems, building multi-agent coordination, evaluating agent performance, or developing LLM-powered pipelines. Covers context fundamentals, degradation patterns, optimization techniques (compaction, masking, caching), compression strategies, memory architectures, multi-agent patterns, LLM-as-Judge evaluation, tool design, and project development.
context-optimizer
openclawAdvanced context management with auto-compaction and dynamic context optimization for DeepSeek's 64k context window. Features intelligent compaction (merging, summarizing, extracting), query-aware relevance scoring, and hierarchical memory system with context archive. Logs optimization events to chat.
cursor-performance-tuning
Optimize Cursor IDE performance. Triggers on "cursor performance", "cursor slow", "cursor optimization", "cursor memory", "speed up cursor". Use when working with cursor performance tuning functionality. Trigger with phrases like "cursor performance tuning", "cursor tuning", "cursor".
windsurf-cascade-context
jeremylongshoreManage Cascade context window and memory for complex projects. Activate when users mention "cascade context", "ai memory", "context management", "large codebase navigation", or "multi-session development". Handles context optimization and persistence. Use when working with windsurf cascade context functionality. Trigger with phrases like "windsurf cascade context", "windsurf context", "windsurf".
profiling-application-performance
jeremylongshoreThis skill enables Claude to profile application performance, analyzing CPU usage, memory consumption, and execution time. It is triggered when the user requests performance analysis, bottleneck identification, or optimization recommendations. The skill uses the application-profiler plugin to identify performance bottlenecks and suggest code-level optimizations. Use it when asked to "profile application", "analyze performance", or "find bottlenecks". It is also helpful when the user mentions specific performance metrics like "CPU usage", "memory leaks", or "execution time".
performance-optimization
FarhanAliRazaApply systematic performance optimization techniques for Python and Rust code: estimation + profiling, API/bulk design, algorithmic wins, cache-friendly memory layout, fewer allocations, fast paths, caching, and compiler-friendly hot loops. Use for performance code reviews, refactors, and profiling-driven optimizations. Keywords: performance, latency, throughput, cache, allocation, memory layout, PyO3, msgspec, tokio, async, pprof, py-spy, perf.
react-native-best-practices
callstackincubatorProvides React Native performance optimization guidelines for FPS, TTI, bundle size, memory leaks, re-renders, and animations. Applies to tasks involving Hermes optimization, JS thread blocking, bridge overhead, FlashList, native modules, or debugging jank and frame drops.
runtime-skills
llama-farmUniversal Runtime best practices for PyTorch inference, Transformers models, and FastAPI serving. Covers device management, model loading, memory optimization, and performance tuning.
memory-optimization
benchflow-aiOptimize Python code for reduced memory usage and improved memory efficiency. Use when asked to reduce memory footprint, fix memory leaks, optimize data structures for memory, handle large datasets efficiently, or diagnose memory issues. Covers object sizing, generator patterns, efficient data structures, and memory profiling strategies.
axiom-ios-performance
Use when app feels slow, memory grows, battery drains, or diagnosing ANY performance issue. Covers memory leaks, profiling, Instruments workflows, retain cycles, performance optimization.
axiom-swift-performance
Use when optimizing Swift code performance, reducing memory usage, improving runtime efficiency, dealing with COW, ARC overhead, generics specialization, or collection optimization
performance-optimization
Identifies and fixes Rails performance issues including N+1 queries, slow queries, and memory problems. Use when optimizing queries, fixing N+1 issues, improving response times, or when user mentions performance, slow, optimization, or Bullet gem.
linker-script
a5c-aiGNU linker script generation and optimization for embedded systems. Expert skill for memory layout definition, section placement, multi-image linking, and memory protection configuration.
gpu-memory-analysis
a5c-aiSpecialized skill for GPU memory hierarchy analysis and optimization. Analyze memory access patterns, detect bank conflicts, optimize cache utilization, profile global memory bandwidth, and generate optimized memory access code patterns.
electron-memory-profiler
a5c-aiProfile Electron app memory usage, detect leaks, analyze renderer process memory, and optimize memory consumption
memory-analysis
a5c-aiEmbedded memory analysis, optimization, and leak detection
pandas-dataframe-analyzer
a5c-aiAutomated DataFrame analysis skill for statistical summaries, missing value detection, data type inference, and memory optimization recommendations.
gas-optimization
a5c-aiAdvanced gas optimization techniques for EVM smart contracts. Covers storage packing, memory vs calldata optimization, assembly/Yul, efficient data structures, batch operations, and benchmark-driven optimization strategies.
distributed-caching
a5c-aiExpert skill for distributed cache design, implementation, and optimization using Redis and Memcached. Design cache architectures, configure eviction policies, implement caching patterns (cache-aside, write-through, write-behind), monitor cache performance, and optimize memory usage.
unified-memory
a5c-aiExpert skill for CUDA Unified Memory and memory prefetching optimization. Configure managed memory allocations, implement memory prefetch strategies, handle page fault analysis, configure memory hints and advise, profile unified memory migration, optimize for oversubscription scenarios, and compare managed vs explicit memory.
unity-profiler
a5c-aiUnity Profiler skill for performance analysis, frame debugging, memory profiling, and optimization workflows.
performance-engineering
ancolemanWhen validating system performance under load, identifying bottlenecks through profiling, or optimizing application responsiveness. Covers load testing (k6, Locust), profiling (CPU, memory, I/O), and optimization strategies (caching, query optimization, Core Web Vitals). Use for capacity planning, regression detection, and establishing performance SLOs.
Flutter Performance
HoangNguyen0403Optimization standards for rebuilds and memory.
V3 Performance Optimization
proffesor-for-testingAchieve aggressive v3 performance targets: 2.49x-7.47x Flash Attention speedup, 150x-12,500x search improvements, 50-75% memory reduction. Comprehensive benchmarking and optimization suite.
AgentDB Performance Optimization
proffesor-for-testingOptimize AgentDB performance with quantization (4-32x memory reduction), HNSW indexing (150x faster search), caching, and batch operations. Use when optimizing memory usage, improving search speed, or scaling to millions of vectors.
aws-agentic-ai
zxkaneAWS Bedrock AgentCore comprehensive expert for deploying and managing all AgentCore services. Use when working with Gateway, Runtime, Memory, Identity, or any AgentCore component. Covers MCP target deployment, credential management, schema optimization, runtime configuration, memory management, and identity services.
agentdb-performance-optimization
aiskillstoreOptimize AgentDB performance with quantization (4-32x memory reduction), HNSW indexing (150x faster search), caching, and batch operations. Use when optimizing memory usage, improving search speed, or scaling to millions of vectors.
agentdb-vector-search-optimization
aiskillstoreOptimize AgentDB vector search performance using quantization for 4-32x memory reduction, HNSW indexing for 150x faster search, caching, and batch operations for scaling to millions of vectors.
react-native-best-practices
alisamadiiiProvides React Native performance optimization guidelines for FPS, TTI, bundle size, memory leaks, re-renders, and animations. Applies to tasks involving Hermes optimization, JS thread blocking, bridge overhead, FlashList, native modules, or debugging jank and frame drops.
claude-md-management
giuseppe-trisciuoglioProvides comprehensive CLAUDE.md file management capabilities including auditing, quality assessment, and targeted improvements. Use when user asks to check, audit, update, improve, fix, maintain, or validate CLAUDE.md files. Also triggers for "project memory optimization", "CLAUDE.md quality check", "documentation review", or when CLAUDE.md needs to be created from scratch. This skill scans all CLAUDE.md files, evaluates quality against standardized criteria, outputs detailed quality reports with scores and recommendations, then makes targeted updates with user approval.
graalvm-native-image
giuseppe-trisciuoglioProvides expert guidance for building GraalVM Native Image executables from Java applications. Use when converting JVM applications to native binaries, optimizing cold start times, reducing memory footprint, configuring native build tools for Maven or Gradle, resolving reflection and resource issues in native builds, or implementing framework-specific native support for Spring Boot, Quarkus, and Micronaut. Triggers include "graalvm native image", "native executable java", "java cold start optimization", "native build tools", "ahead of time compilation java", "reflection config graalvm", "native image build failure".
performance
Piebald-AIPerformance optimization guidelines for Splitrail. Use when optimizing parsing, reducing memory usage, or improving throughput.