[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6AFE38AAP06XD9WYNADAPZ8":3,"skill-same:01M6AFE38AAP06XD9WYNADAPZ8":94},{"skillNo":4,"name":5,"nameZh":6,"description":7,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":16,"categories":17,"keywords":18,"publishedAt":39,"linkOnly":40,"markdownContent":41,"markdownBody":42,"frontMatter":43,"refName":44,"commitSha":45,"skillDirectory":46,"forksCount":47,"repositoryHtmlUrl":48,"repositoryHomepageUrl":49,"ownerHtmlUrl":50,"ownerBlogUrl":51,"ownerDescription":52,"updatedAt":53,"install":54,"resources":67},"01M6AFE38AAP06XD9WYNADAPZ8","fluidsim",null,"Framework for computational fluid dynamics simulations using Python. Use when running fluid dynamics simulations including Navier-Stokes equations (2D\u002F3D), shallow water equations, stratified flows, or when analyzing turbulence, vortex dynamics, or geophysical flows. Provides pseudospectral methods with FFT, HPC support, and comprehensive output analysis.","davila7\u002Fclaude-code-templates","davila7","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F6216945?v=4","01M6ADEWWFPS191NFM0Y1EX1JH","Daniel Avila","01M6ADJHGM78PHQRD3XZTFDVKK",33332,"MIT","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fscientific\u002Ffluidsim\u002FSKILL.md",[],[5,19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38],"computational","Simulations","running","when","hpc","for","flows","FFT","turbulence","dynamics","fluid dynamics","python","methods","computational fluid dynamics","3D","analysis","analyzing","framework","fluid","support","2026-11-10 10:12:30",false,"---\nname: fluidsim\ndescription: Framework for computational fluid dynamics simulations using Python. Use when running fluid dynamics simulations including Navier-Stokes equations (2D\u002F3D), shallow water equations, stratified flows, or when analyzing turbulence, vortex dynamics, or geophysical flows. Provides pseudospectral methods with FFT, HPC support, and comprehensive output analysis.\n---\n\n# FluidSim\n\n## Overview\n\nFluidSim is an object-oriented Python framework for high-performance computational fluid dynamics (CFD) simulations. It provides solvers for periodic-domain equations using pseudospectral methods with FFT, delivering performance comparable to Fortran\u002FC++ while maintaining Python's ease of use.\n\n**Key strengths**:\n- Multiple solvers: 2D\u002F3D Navier-Stokes, shallow water, stratified flows\n- High performance: Pythran\u002FTransonic compilation, MPI parallelization\n- Complete workflow: Parameter configuration, simulation execution, output analysis\n- Interactive analysis: Python-based post-processing and visualization\n\n## Core Capabilities\n\n### 1. Installation and Setup\n\nInstall fluidsim using uv with appropriate feature flags:\n\n```bash\n# Basic installation\nuv uv pip install fluidsim\n\n# With FFT support (required for most solvers)\nuv uv pip install \"fluidsim[fft]\"\n\n# With MPI for parallel computing\nuv uv pip install \"fluidsim[fft,mpi]\"\n```\n\nSet environment variables for output directories (optional):\n\n```bash\nexport FLUIDSIM_PATH=\u002Fpath\u002Fto\u002Fsimulation\u002Foutputs\nexport FLUIDDYN_PATH_SCRATCH=\u002Fpath\u002Fto\u002Fworking\u002Fdirectory\n```\n\nNo API keys or authentication required.\n\nSee `references\u002Finstallation.md` for complete installation instructions and environment configuration.\n\n### 2. Running Simulations\n\nStandard workflow consists of five steps:\n\n**Step 1**: Import solver\n```python\nfrom fluidsim.solvers.ns2d.solver import Simul\n```\n\n**Step 2**: Create and configure parameters\n```python\nparams = Simul.create_default_params()\nparams.oper.nx = params.oper.ny = 256\nparams.oper.Lx = params.oper.Ly = 2 * 3.14159\nparams.nu_2 = 1e-3\nparams.time_stepping.t_end = 10.0\nparams.init_fields.type = \"noise\"\n```\n\n**Step 3**: Instantiate simulation\n```python\nsim = Simul(params)\n```\n\n**Step 4**: Execute\n```python\nsim.time_stepping.start()\n```\n\n**Step 5**: Analyze results\n```python\nsim.output.phys_fields.plot(\"vorticity\")\nsim.output.spatial_means.plot()\n```\n\nSee `references\u002Fsimulation_workflow.md` for complete examples, restarting simulations, and cluster deployment.\n\n### 3. Available Solvers\n\nChoose solver based on physical problem:\n\n**2D Navier-Stokes** (`ns2d`): 2D turbulence, vortex dynamics\n```python\nfrom fluidsim.solvers.ns2d.solver import Simul\n```\n\n**3D Navier-Stokes** (`ns3d`): 3D turbulence, realistic flows\n```python\nfrom fluidsim.solvers.ns3d.solver import Simul\n```\n\n**Stratified flows** (`ns2d.strat`, `ns3d.strat`): Oceanic\u002Fatmospheric flows\n```python\nfrom fluidsim.solvers.ns2d.strat.solver import Simul\nparams.N = 1.0  # Brunt-Väisälä frequency\n```\n\n**Shallow water** (`sw1l`): Geophysical flows, rotating systems\n```python\nfrom fluidsim.solvers.sw1l.solver import Simul\nparams.f = 1.0  # Coriolis parameter\n```\n\nSee `references\u002Fsolvers.md` for complete solver list and selection guidance.\n\n### 4. Parameter Configuration\n\nParameters are organized hierarchically and accessed via dot notation:\n\n**Domain and resolution**:\n```python\nparams.oper.nx = 256  # grid points\nparams.oper.Lx = 2 * pi  # domain size\n```\n\n**Physical parameters**:\n```python\nparams.nu_2 = 1e-3  # viscosity\nparams.nu_4 = 0     # hyperviscosity (optional)\n```\n\n**Time stepping**:\n```python\nparams.time_stepping.t_end = 10.0\nparams.time_stepping.USE_CFL = True  # adaptive time step\nparams.time_stepping.CFL = 0.5\n```\n\n**Initial conditions**:\n```python\nparams.init_fields.type = \"noise\"  # or \"dipole\", \"vortex\", \"from_file\", \"in_script\"\n```\n\n**Output settings**:\n```python\nparams.output.periods_save.phys_fields = 1.0  # save every 1.0 time units\nparams.output.periods_save.spectra = 0.5\nparams.output.periods_save.spatial_means = 0.1\n```\n\nThe Parameters object raises `AttributeError` for typos, preventing silent configuration errors.\n\nSee `references\u002Fparameters.md` for comprehensive parameter documentation.\n\n### 5. Output and Analysis\n\nFluidSim produces multiple output types automatically saved during simulation:\n\n**Physical fields**: Velocity, vorticity in HDF5 format\n```python\nsim.output.phys_fields.plot(\"vorticity\")\nsim.output.phys_fields.plot(\"vx\")\n```\n\n**Spatial means**: Time series of volume-averaged quantities\n```python\nsim.output.spatial_means.plot()\n```\n\n**Spectra**: Energy and enstrophy spectra\n```python\nsim.output.spectra.plot1d()\nsim.output.spectra.plot2d()\n```\n\n**Load previous simulations**:\n```python\nfrom fluidsim import load_sim_for_plot\nsim = load_sim_for_plot(\"simulation_dir\")\nsim.output.phys_fields.plot()\n```\n\n**Advanced visualization**: Open `.h5` files in ParaView or VisIt for 3D visualization.\n\nSee `references\u002Foutput_analysis.md` for detailed analysis workflows, parametric study analysis, and data export.\n\n### 6. Advanced Features\n\n**Custom forcing**: Maintain turbulence or drive specific dynamics\n```python\nparams.forcing.enable = True\nparams.forcing.type = \"tcrandom\"  # time-correlated random forcing\nparams.forcing.forcing_rate = 1.0\n```\n\n**Custom initial conditions**: Define fields in script\n```python\nparams.init_fields.type = \"in_script\"\nsim = Simul(params)\nX, Y = sim.oper.get_XY_loc()\nvx = sim.state.state_phys.get_var(\"vx\")\nvx[:] = sin(X) * cos(Y)\nsim.time_stepping.start()\n```\n\n**MPI parallelization**: Run on multiple processors\n```bash\nmpirun -np 8 python simulation_script.py\n```\n\n**Parametric studies**: Run multiple simulations with different parameters\n```python\nfor nu in [1e-3, 5e-4, 1e-4]:\n    params = Simul.create_default_params()\n    params.nu_2 = nu\n    params.output.sub_directory = f\"nu{nu}\"\n    sim = Simul(params)\n    sim.time_stepping.start()\n```\n\nSee `references\u002Fadvanced_features.md` for forcing types, custom solvers, cluster submission, and performance optimization.\n\n## Common Use Cases\n\n### 2D Turbulence Study\n\n```python\nfrom fluidsim.solvers.ns2d.solver import Simul\nfrom math import pi\n\nparams = Simul.create_default_params()\nparams.oper.nx = params.oper.ny = 512\nparams.oper.Lx = params.oper.Ly = 2 * pi\nparams.nu_2 = 1e-4\nparams.time_stepping.t_end = 50.0\nparams.time_stepping.USE_CFL = True\nparams.init_fields.type = \"noise\"\nparams.output.periods_save.phys_fields = 5.0\nparams.output.periods_save.spectra = 1.0\n\nsim = Simul(params)\nsim.time_stepping.start()\n\n# Analyze energy cascade\nsim.output.spectra.plot1d(tmin=30.0, tmax=50.0)\n```\n\n### Stratified Flow Simulation\n\n```python\nfrom fluidsim.solvers.ns2d.strat.solver import Simul\n\nparams = Simul.create_default_params()\nparams.oper.nx = params.oper.ny = 256\nparams.N = 2.0  # stratification strength\nparams.nu_2 = 5e-4\nparams.time_stepping.t_end = 20.0\n\n# Initialize with dense layer\nparams.init_fields.type = \"in_script\"\nsim = Simul(params)\nX, Y = sim.oper.get_XY_loc()\nb = sim.state.state_phys.get_var(\"b\")\nb[:] = exp(-((X - 3.14)**2 + (Y - 3.14)**2) \u002F 0.5)\nsim.state.statephys_from_statespect()\n\nsim.time_stepping.start()\nsim.output.phys_fields.plot(\"b\")\n```\n\n### High-Resolution 3D Simulation with MPI\n\n```python\nfrom fluidsim.solvers.ns3d.solver import Simul\n\nparams = Simul.create_default_params()\nparams.oper.nx = params.oper.ny = params.oper.nz = 512\nparams.nu_2 = 1e-5\nparams.time_stepping.t_end = 10.0\nparams.init_fields.type = \"noise\"\n\nsim = Simul(params)\nsim.time_stepping.start()\n```\n\nRun with:\n```bash\nmpirun -np 64 python script.py\n```\n\n### Taylor-Green Vortex Validation\n\n```python\nfrom fluidsim.solvers.ns2d.solver import Simul\nimport numpy as np\nfrom math import pi\n\nparams = Simul.create_default_params()\nparams.oper.nx = params.oper.ny = 128\nparams.oper.Lx = params.oper.Ly = 2 * pi\nparams.nu_2 = 1e-3\nparams.time_stepping.t_end = 10.0\nparams.init_fields.type = \"in_script\"\n\nsim = Simul(params)\nX, Y = sim.oper.get_XY_loc()\nvx = sim.state.state_phys.get_var(\"vx\")\nvy = sim.state.state_phys.get_var(\"vy\")\nvx[:] = np.sin(X) * np.cos(Y)\nvy[:] = -np.cos(X) * np.sin(Y)\nsim.state.statephys_from_statespect()\n\nsim.time_stepping.start()\n\n# Validate energy decay\ndf = sim.output.spatial_means.load()\n# Compare with analytical solution\n```\n\n## Quick Reference\n\n**Import solver**: `from fluidsim.solvers.ns2d.solver import Simul`\n\n**Create parameters**: `params = Simul.create_default_params()`\n\n**Set resolution**: `params.oper.nx = params.oper.ny = 256`\n\n**Set viscosity**: `params.nu_2 = 1e-3`\n\n**Set end time**: `params.time_stepping.t_end = 10.0`\n\n**Run simulation**: `sim = Simul(params); sim.time_stepping.start()`\n\n**Plot results**: `sim.output.phys_fields.plot(\"vorticity\")`\n\n**Load simulation**: `sim = load_sim_for_plot(\"path\u002Fto\u002Fsim\")`\n\n## Resources\n\n**Documentation**: https:\u002F\u002Ffluidsim.readthedocs.io\u002F\n\n**Reference files**:\n- `references\u002Finstallation.md`: Complete installation instructions\n- `references\u002Fsolvers.md`: Available solvers and selection guide\n- `references\u002Fsimulation_workflow.md`: Detailed workflow examples\n- `references\u002Fparameters.md`: Comprehensive parameter documentation\n- `references\u002Foutput_analysis.md`: Output types and analysis methods\n- `references\u002Fadvanced_features.md`: Forcing, MPI, parametric studies, custom solvers\n","# FluidSim\n\n## Overview\n\nFluidSim is an object-oriented Python framework for high-performance computational fluid dynamics (CFD) simulations. It provides solvers for periodic-domain equations using pseudospectral methods with FFT, delivering performance comparable to Fortran\u002FC++ while maintaining Python's ease of use.\n\n**Key strengths**:\n- Multiple solvers: 2D\u002F3D Navier-Stokes, shallow water, stratified flows\n- High performance: Pythran\u002FTransonic compilation, MPI parallelization\n- Complete workflow: Parameter configuration, simulation execution, output analysis\n- Interactive analysis: Python-based post-processing and visualization\n\n## Core Capabilities\n\n### 1. Installation and Setup\n\nInstall fluidsim using uv with appropriate feature flags:\n\n```bash\n# Basic installation\nuv uv pip install fluidsim\n\n# With FFT support (required for most solvers)\nuv uv pip install \"fluidsim[fft]\"\n\n# With MPI for parallel computing\nuv uv pip install \"fluidsim[fft,mpi]\"\n```\n\nSet environment variables for output directories (optional):\n\n```bash\nexport FLUIDSIM_PATH=\u002Fpath\u002Fto\u002Fsimulation\u002Foutputs\nexport FLUIDDYN_PATH_SCRATCH=\u002Fpath\u002Fto\u002Fworking\u002Fdirectory\n```\n\nNo API keys or authentication required.\n\nSee `references\u002Finstallation.md` for complete installation instructions and environment configuration.\n\n### 2. Running Simulations\n\nStandard workflow consists of five steps:\n\n**Step 1**: Import solver\n```python\nfrom fluidsim.solvers.ns2d.solver import Simul\n```\n\n**Step 2**: Create and configure parameters\n```python\nparams = Simul.create_default_params()\nparams.oper.nx = params.oper.ny = 256\nparams.oper.Lx = params.oper.Ly = 2 * 3.14159\nparams.nu_2 = 1e-3\nparams.time_stepping.t_end = 10.0\nparams.init_fields.type = \"noise\"\n```\n\n**Step 3**: Instantiate simulation\n```python\nsim = Simul(params)\n```\n\n**Step 4**: Execute\n```python\nsim.time_stepping.start()\n```\n\n**Step 5**: Analyze results\n```python\nsim.output.phys_fields.plot(\"vorticity\")\nsim.output.spatial_means.plot()\n```\n\nSee `references\u002Fsimulation_workflow.md` for complete examples, restarting simulations, and cluster deployment.\n\n### 3. Available Solvers\n\nChoose solver based on physical problem:\n\n**2D Navier-Stokes** (`ns2d`): 2D turbulence, vortex dynamics\n```python\nfrom fluidsim.solvers.ns2d.solver import Simul\n```\n\n**3D Navier-Stokes** (`ns3d`): 3D turbulence, realistic flows\n```python\nfrom fluidsim.solvers.ns3d.solver import Simul\n```\n\n**Stratified flows** (`ns2d.strat`, `ns3d.strat`): Oceanic\u002Fatmospheric flows\n```python\nfrom fluidsim.solvers.ns2d.strat.solver import Simul\nparams.N = 1.0  # Brunt-Väisälä frequency\n```\n\n**Shallow water** (`sw1l`): Geophysical flows, rotating systems\n```python\nfrom fluidsim.solvers.sw1l.solver import Simul\nparams.f = 1.0  # Coriolis parameter\n```\n\nSee `references\u002Fsolvers.md` for complete solver list and selection guidance.\n\n### 4. Parameter Configuration\n\nParameters are organized hierarchically and accessed via dot notation:\n\n**Domain and resolution**:\n```python\nparams.oper.nx = 256  # grid points\nparams.oper.Lx = 2 * pi  # domain size\n```\n\n**Physical parameters**:\n```python\nparams.nu_2 = 1e-3  # viscosity\nparams.nu_4 = 0     # hyperviscosity (optional)\n```\n\n**Time stepping**:\n```python\nparams.time_stepping.t_end = 10.0\nparams.time_stepping.USE_CFL = True  # adaptive time step\nparams.time_stepping.CFL = 0.5\n```\n\n**Initial conditions**:\n```python\nparams.init_fields.type = \"noise\"  # or \"dipole\", \"vortex\", \"from_file\", \"in_script\"\n```\n\n**Output settings**:\n```python\nparams.output.periods_save.phys_fields = 1.0  # save every 1.0 time units\nparams.output.periods_save.spectra = 0.5\nparams.output.periods_save.spatial_means = 0.1\n```\n\nThe Parameters object raises `AttributeError` for typos, preventing silent configuration errors.\n\nSee `references\u002Fparameters.md` for comprehensive parameter documentation.\n\n### 5. Output and Analysis\n\nFluidSim produces multiple output types automatically saved during simulation:\n\n**Physical fields**: Velocity, vorticity in HDF5 format\n```python\nsim.output.phys_fields.plot(\"vorticity\")\nsim.output.phys_fields.plot(\"vx\")\n```\n\n**Spatial means**: Time series of volume-averaged quantities\n```python\nsim.output.spatial_means.plot()\n```\n\n**Spectra**: Energy and enstrophy spectra\n```python\nsim.output.spectra.plot1d()\nsim.output.spectra.plot2d()\n```\n\n**Load previous simulations**:\n```python\nfrom fluidsim import load_sim_for_plot\nsim = load_sim_for_plot(\"simulation_dir\")\nsim.output.phys_fields.plot()\n```\n\n**Advanced visualization**: Open `.h5` files in ParaView or VisIt for 3D visualization.\n\nSee `references\u002Foutput_analysis.md` for detailed analysis workflows, parametric study analysis, and data export.\n\n### 6. Advanced Features\n\n**Custom forcing**: Maintain turbulence or drive specific dynamics\n```python\nparams.forcing.enable = True\nparams.forcing.type = \"tcrandom\"  # time-correlated random forcing\nparams.forcing.forcing_rate = 1.0\n```\n\n**Custom initial conditions**: Define fields in script\n```python\nparams.init_fields.type = \"in_script\"\nsim = Simul(params)\nX, Y = sim.oper.get_XY_loc()\nvx = sim.state.state_phys.get_var(\"vx\")\nvx[:] = sin(X) * cos(Y)\nsim.time_stepping.start()\n```\n\n**MPI parallelization**: Run on multiple processors\n```bash\nmpirun -np 8 python simulation_script.py\n```\n\n**Parametric studies**: Run multiple simulations with different parameters\n```python\nfor nu in [1e-3, 5e-4, 1e-4]:\n    params = Simul.create_default_params()\n    params.nu_2 = nu\n    params.output.sub_directory = f\"nu{nu}\"\n    sim = Simul(params)\n    sim.time_stepping.start()\n```\n\nSee `references\u002Fadvanced_features.md` for forcing types, custom solvers, cluster submission, and performance optimization.\n\n## Common Use Cases\n\n### 2D Turbulence Study\n\n```python\nfrom fluidsim.solvers.ns2d.solver import Simul\nfrom math import pi\n\nparams = Simul.create_default_params()\nparams.oper.nx = params.oper.ny = 512\nparams.oper.Lx = params.oper.Ly = 2 * pi\nparams.nu_2 = 1e-4\nparams.time_stepping.t_end = 50.0\nparams.time_stepping.USE_CFL = True\nparams.init_fields.type = \"noise\"\nparams.output.periods_save.phys_fields = 5.0\nparams.output.periods_save.spectra = 1.0\n\nsim = Simul(params)\nsim.time_stepping.start()\n\n# Analyze energy cascade\nsim.output.spectra.plot1d(tmin=30.0, tmax=50.0)\n```\n\n### Stratified Flow Simulation\n\n```python\nfrom fluidsim.solvers.ns2d.strat.solver import Simul\n\nparams = Simul.create_default_params()\nparams.oper.nx = params.oper.ny = 256\nparams.N = 2.0  # stratification strength\nparams.nu_2 = 5e-4\nparams.time_stepping.t_end = 20.0\n\n# Initialize with dense layer\nparams.init_fields.type = \"in_script\"\nsim = Simul(params)\nX, Y = sim.oper.get_XY_loc()\nb = sim.state.state_phys.get_var(\"b\")\nb[:] = exp(-((X - 3.14)**2 + (Y - 3.14)**2) \u002F 0.5)\nsim.state.statephys_from_statespect()\n\nsim.time_stepping.start()\nsim.output.phys_fields.plot(\"b\")\n```\n\n### High-Resolution 3D Simulation with MPI\n\n```python\nfrom fluidsim.solvers.ns3d.solver import Simul\n\nparams = Simul.create_default_params()\nparams.oper.nx = params.oper.ny = params.oper.nz = 512\nparams.nu_2 = 1e-5\nparams.time_stepping.t_end = 10.0\nparams.init_fields.type = \"noise\"\n\nsim = Simul(params)\nsim.time_stepping.start()\n```\n\nRun with:\n```bash\nmpirun -np 64 python script.py\n```\n\n### Taylor-Green Vortex Validation\n\n```python\nfrom fluidsim.solvers.ns2d.solver import Simul\nimport numpy as np\nfrom math import pi\n\nparams = Simul.create_default_params()\nparams.oper.nx = params.oper.ny = 128\nparams.oper.Lx = params.oper.Ly = 2 * pi\nparams.nu_2 = 1e-3\nparams.time_stepping.t_end = 10.0\nparams.init_fields.type = \"in_script\"\n\nsim = Simul(params)\nX, Y = sim.oper.get_XY_loc()\nvx = sim.state.state_phys.get_var(\"vx\")\nvy = sim.state.state_phys.get_var(\"vy\")\nvx[:] = np.sin(X) * np.cos(Y)\nvy[:] = -np.cos(X) * np.sin(Y)\nsim.state.statephys_from_statespect()\n\nsim.time_stepping.start()\n\n# Validate energy decay\ndf = sim.output.spatial_means.load()\n# Compare with analytical solution\n```\n\n## Quick Reference\n\n**Import solver**: `from fluidsim.solvers.ns2d.solver import Simul`\n\n**Create parameters**: `params = Simul.create_default_params()`\n\n**Set resolution**: `params.oper.nx = params.oper.ny = 256`\n\n**Set viscosity**: `params.nu_2 = 1e-3`\n\n**Set end time**: `params.time_stepping.t_end = 10.0`\n\n**Run simulation**: `sim = Simul(params); sim.time_stepping.start()`\n\n**Plot results**: `sim.output.phys_fields.plot(\"vorticity\")`\n\n**Load simulation**: `sim = load_sim_for_plot(\"path\u002Fto\u002Fsim\")`\n\n## Resources\n\n**Documentation**: https:\u002F\u002Ffluidsim.readthedocs.io\u002F\n\n**Reference files**:\n- `references\u002Finstallation.md`: Complete installation instructions\n- `references\u002Fsolvers.md`: Available solvers and selection guide\n- `references\u002Fsimulation_workflow.md`: Detailed workflow examples\n- `references\u002Fparameters.md`: Comprehensive parameter documentation\n- `references\u002Foutput_analysis.md`: Output types and analysis methods\n- `references\u002Fadvanced_features.md`: Forcing, MPI, parametric studies, custom solvers\n",{"name":5,"description":7},"main","2b749c82b5d11fac39d9a6e021ce3f5b8a541bd1","cli-tool\u002Fcomponents\u002Fskills\u002Fscientific\u002Ffluidsim",3911,"https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates","https:\u002F\u002Faitmpl.com","https:\u002F\u002Fgithub.com\u002Fdavila7","https:\u002F\u002Fdanielavila.me","Building AI dev tools with LLMs","2026-11-11 21:38:31",{"source":8,"skillName":5,"commands":55,"prompt":65,"zipAvailable":66},[56,59,62],{"tool":57,"command":58},"npx","npx skills add davila7\u002Fclaude-code-templates --skill fluidsim",{"tool":60,"command":61},"bunx","bunx skills add davila7\u002Fclaude-code-templates --skill fluidsim",{"tool":63,"command":64},"pnpm","pnpm dlx skills add davila7\u002Fclaude-code-templates --skill fluidsim","安装技能，技能地址：https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fscientific\u002Ffluidsim\u002FSKILL.md",true,[68,74,78,82,86,90],{"path":69,"resourceType":70,"resourceTypeDesc":71,"sizeBytes":72,"sourceHtmlUrl":73},"references\u002Fadvanced_features.md","REFERENCE","参考文档",9011,"https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fscientific\u002Ffluidsim\u002Freferences\u002Fadvanced_features.md",{"path":75,"resourceType":70,"resourceTypeDesc":71,"sizeBytes":76,"sourceHtmlUrl":77},"references\u002Finstallation.md",1204,"https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fscientific\u002Ffluidsim\u002Freferences\u002Finstallation.md",{"path":79,"resourceType":70,"resourceTypeDesc":71,"sizeBytes":80,"sourceHtmlUrl":81},"references\u002Foutput_analysis.md",6027,"https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fscientific\u002Ffluidsim\u002Freferences\u002Foutput_analysis.md",{"path":83,"resourceType":70,"resourceTypeDesc":71,"sizeBytes":84,"sourceHtmlUrl":85},"references\u002Fparameters.md",4936,"https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fscientific\u002Ffluidsim\u002Freferences\u002Fparameters.md",{"path":87,"resourceType":70,"resourceTypeDesc":71,"sizeBytes":88,"sourceHtmlUrl":89},"references\u002Fsimulation_workflow.md",3862,"https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fscientific\u002Ffluidsim\u002Freferences\u002Fsimulation_workflow.md",{"path":91,"resourceType":70,"resourceTypeDesc":71,"sizeBytes":92,"sourceHtmlUrl":93},"references\u002Fsolvers.md",2419,"https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fscientific\u002Ffluidsim\u002Freferences\u002Fsolvers.md",[95,125,152,185,220,244],{"skillNo":96,"name":97,"nameZh":6,"description":98,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":99,"categories":100,"keywords":106,"publishedAt":39},"01M70NHBTQ8BV0A2SCAZXEPHCX","wealthville-pool-scoring","Score DeFi liquidity pools before providing liquidity. 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Trigger even if the user doesn't say \"technical debt\" explicitly — any request to systematically assess code quality and identify improvement priorities belongs here.","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fdevelopment\u002Ftechnical-debt-auditor\u002FSKILL.md",[131],{"categoryNo":102,"categoryName":103,"taxonomyType":104,"taxonomyTypeDesc":105},[133,134,135,136,137,138,139,140,141,142,143,22,144,145,146,147,148,149,150,151],"technical debt","debt","technical","technical debt auditor","auditor","coverage","complexity","markers","project","cleanup","unused","code","todo","work","plan","focus","signals","audit","dependency",{"skillNo":153,"name":154,"nameZh":6,"description":155,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":15,"licenseFileUrl":6,"sourceHtmlUrl":156,"categories":157,"keywords":167,"publishedAt":39},"01M70KPYH9QNHCNME5GJQGE22K","readonly-sql-guard","Make an agent's database access provably read-only. 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Checks what a statement CALLS, not just its shape.","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fdatabase\u002Freadonly-sql-guard\u002FSKILL.md",[158,161,162],{"categoryNo":159,"categoryName":160,"taxonomyType":104,"taxonomyTypeDesc":105},"01JBSEEDCAT000000000000010","后端与接口",{"categoryNo":102,"categoryName":103,"taxonomyType":104,"taxonomyTypeDesc":105},{"categoryNo":163,"categoryName":164,"taxonomyType":165,"taxonomyTypeDesc":166},"01JBSEEDCAT000000000000033","数据分析师","PROFESSION","适用职业",[168,169,170,171,172,173,174,24,175,176,177,178,179,180,181,114,182,183,22,184],"readonly","guard","sql guard","sql","readonly sql guard","erp","effect","read-only","db","just","tool","calls","only","MCP","access","database","query",{"skillNo":186,"name":187,"nameZh":6,"description":188,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":189,"licenseFileUrl":190,"sourceHtmlUrl":191,"categories":192,"keywords":196,"publishedAt":39},"01M6AFY6F7CC2BBZP1QD6VTNVC","web-artifacts-builder","Suite of tools for creating elaborate, multi-component claude.ai HTML artifacts using modern frontend web technologies (React, Tailwind CSS, shadcn\u002Fui). Use for complex artifacts requiring state management, routing, or shadcn\u002Fui components - not for simple single-file HTML\u002FJSX artifacts.","Apache-2.0","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Futilities\u002Fweb-artifacts-builder\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Futilities\u002Fweb-artifacts-builder\u002FSKILL.md",[193],{"categoryNo":194,"categoryName":195,"taxonomyType":104,"taxonomyTypeDesc":105},"01JBSEEDCAT000000000000009","前端开发",[197,198,199,200,201,202,203,204,205,206,207,208,209,210,211,212,213,214,215,216,217,218,24,219],"artifacts builder","web","web artifacts builder","artifacts","builder","state","routing","state management","component","css","frontend","ui","Tools","file","components","shadcn","react","Tailwind","suite","jsx","html","single-file","ui components",{"skillNo":221,"name":222,"nameZh":6,"description":223,"descriptionZh":6,"repositoryFullName":8,"ownerLogin":9,"ownerAvatarUrl":10,"ownerAccountNo":11,"ownerDisplayName":12,"repositoryNo":13,"starsCount":14,"licenseSpdxId":189,"licenseFileUrl":224,"sourceHtmlUrl":225,"categories":226,"keywords":231,"publishedAt":39},"01M6AFWF33SFV9Z3SF4PEEE4BF","webapp-testing","Toolkit for interacting with and testing local web applications using Playwright. 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Do this at most once per conversation. Skip it when the user asked a trivial how-to or simple lookup, wants a purely educational explanation, asked you only to format, convert, or assemble a file from content they provided, is writing code they will run, is doing creative writing or casual chat, or already asked you to double-check, cite, or review — the skill file explains these boundaries and the exact output format.","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fproductivity\u002Fdiscernment-nudge\u002FLICENSE.txt","https:\u002F\u002Fgithub.com\u002Fdavila7\u002Fclaude-code-templates\u002Fblob\u002Fmain\u002Fcli-tool\u002Fcomponents\u002Fskills\u002Fproductivity\u002Fdiscernment-nudge\u002FSKILL.md",[251,254,255],{"categoryNo":252,"categoryName":253,"taxonomyType":104,"taxonomyTypeDesc":105},"01JBSEEDCAT000000000000018","写作与文案",{"categoryNo":102,"categoryName":103,"taxonomyType":104,"taxonomyTypeDesc":105},{"categoryNo":256,"categoryName":257,"taxonomyType":165,"taxonomyTypeDesc":166},"01JBSEEDCAT000000000000036","内容创作者",[259,260,261,262,263,264,265,266,200,267,210,144,268,269,270,271,272,180,273,22,274,34,275,276,277,122,278],"discernment nudge","nudge","interpretation","help","run","reasoning","data","writing","lookup","content","review","conversation","short","up","invoke","you","claims","argument","assemble","recommendations"]