By datathings
Develop cross-platform GPU/CPU parallel computing applications in C/C++ with OpenCL SDK, managing devices, contexts, queues, kernels, buffers, images, programs, and using C++ bindings for heterogeneous acceleration.
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npx claudepluginhub datathings/marketplace --plugin openclpower-grid-model Python skill - high-performance steady-state distribution power system analysis: power flow, state estimation, and IEC 60909 short-circuit calculations with 22 component types and batch/parallel computation
Complete llama.cpp C/C++ API reference (v b7885) covering 198 functions: model loading, inference, text generation, embeddings, chat, advanced sampling (XTC, DRY, infill), per-sequence state management, model type detection, and more. For GGUF models, local LLM inference, and C/C++ AI development.
Comprehensive GreyCat development skill for graph-based language with built-in persistence. Covers data modeling, API development, parallel processing, frontend integration, and all standard libraries.
pandapower v3.4.0 Python skill - power systems analysis with 80+ functions for AC/DC power flow, OPF, short circuit (IEC 60909), and state estimation
ggml v0.9.7 C tensor library skill — 560+ functions for graph computation, GGUF I/O, multi-backend inference, and ML training
NVIDIA CUDA C/C++ skill - Runtime API, cuBLAS, cuFFT, cuSPARSE, cuRAND, cuSolver, Thrust, and Cooperative Groups for GPU-accelerated computing
GPU kernel knowledge-base, benchmarking, profiling, and optimization-loop skills for CUDA, Triton, CuTe DSL, CUTLASS, PyTorch, and Nsight Compute workflows.
Graphics engineering agents providing expertise in GPU programming, shaders, and rendering
Claude Code skill pack for CoreWeave (24 skills)
Node Hardware MCP - Comprehensive Hardware Monitoring and System Analysis for LLMs with real-time performance metrics
Skills for NVIDIAs ecosystem spans GPU acceleration, CUDA, AI agents, inference, robotics, Physical AI, Omniverse, and simulation. This plugin helps you understand the pieces, choose a path, validate your setup, and build practical NVIDIA-powered workflows.