AI Agent Workflow Collection

Complete CBLAS and LAPACKE C API reference (LAPACK v3.12.1) covering 1284 functions for numerical linear algebra: BLAS Level 1/2/3 vector and matrix operations, linear system solvers (LU, Cholesky, LDL), eigenvalue/eigenvector computation, singular value decomposition, least squares, QR/LQ factorizations, and auxiliary routines. Triggers on: BLAS/LAPACK questions, CBLAS/LAPACKE code, linear algebra in C/C++, matrix operations, numerical computing, scientific computing, HPC, linking BLAS/LAPACK.

C tensor computation library for ML inference and training. Use when working with ggml graphs, GGUF model files, backend scheduling, quantization, or implementing low-level ML ops in C/C++.

Build, run, and edit GreyCat projects. GreyCat is a statically-typed language plus runtime for graph-persistent, time-series-aware applications. Use when reading or writing .gcl source, when the user mentions GreyCat / project.gcl / nodeTime / nodeList / nodeIndex / nodeGeo / @expose / @library, or when the task involves running greycat , deploying a project, or reasoning about gcdata/, lib/, files/, webroot/.

OpenCL SDK (Khronos Group) for cross-platform GPU/CPU parallel computing in C and C++. Use when writing OpenCL kernels, managing devices/contexts/queues, allocating and transferring buffers or images, building and executing programs, or using the C++ wrapper (opencl.hpp / cl::CommandQueue, cl::Buffer, cl::KernelFunctor). Covers OpenCL C API, C++ bindings, and SDK utility libraries (OpenCLUtils, OpenCLSDK).

Power systems analysis and optimization library (pandapower v3.4.0). Use when working with electric power networks: building network models (buses, lines, transformers, loads, generators), running AC/DC power flow, optimal power flow (OPF), short circuit calculations (IEC 60909), state estimation, time series simulations, network topology analysis, or visualizing power grids in Python.

Python library for steady-state distribution power system analysis (power flow, state estimation, short-circuit calculations). Use when working with the power-grid-model library to: (1) perform load flow or Newton-Raphson/iterative calculations on electrical grids, (2) run state estimation with sensor data, (3) compute IEC 60909 short-circuit currents, (4) execute batch/time-series or N-1 contingency simulations, or (5) work with grid component types (node, line, transformer, source, symload, etc.) and numpy structured arrays.

AMD ROCm GPU computing stack for HIP kernel development and GPU-accelerated library usage. Use when: writing HIP kernels (.hip files), using rocBLAS/rocFFT/rocRAND/rocSOLVER/rocSPARSE/hipBLAS/hipBLASLt/hipTensor/hipSPARSELt/rocALUTION compute libraries, profiling with rocProfiler or rocprof, porting CUDA code to HIP, building CMake/Makefile projects targeting AMD GPUs, using HIP Graphs for low-overhead kernel replay, or debugging GPU code with rocGDB.