[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"skill:01M6J9MFVJB0169PC0YCFEPCD3":3,"skill-same:01M6J9MFVJB0169PC0YCFEPCD3":79},{"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":44,"linkOnly":45,"markdownContent":46,"markdownBody":47,"frontMatter":48,"refName":58,"commitSha":59,"skillDirectory":60,"forksCount":52,"repositoryHtmlUrl":61,"repositoryHomepageUrl":6,"ownerHtmlUrl":62,"ownerBlogUrl":63,"ownerDescription":64,"updatedAt":65,"install":66,"resources":78},"01M6J9MFVJB0169PC0YCFEPCD3","science-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.","Flissel\u002Fvibemind-os","Flissel","https:\u002F\u002Favatars.githubusercontent.com\u002Fu\u002F104565236?v=4","01M6J8Q88NWAJGKPC5TEG9YCNV","Felix Baumann","01M6J8Q8D7XAFY44P70XTJFZBW",1,"MIT","https:\u002F\u002Fgithub.com\u002FFlissel\u002Fvibemind-os\u002Fblob\u002Fmaster\u002Fskills\u002Fscience\u002Ffluidsim\u002FSKILL.md",[],[19,20,21,22,23,24,25,26,27,28,29,30,31,32,33,34,35,36,37,38,39,40,41,42,43],"fluidsim","science","science fluidsim","fluid dynamics","Simulations","2026","running","when","hpc","source","for","flows","FFT","turbulence","dynamics","support","computational","imported","methods","computational fluid dynamics","repo","3D","analysis","analyzing","framework","2026-11-10 10:12:30",false,"---\nname: science-fluidsim\ndescription: Framework for computational fluid dynamics simulations using Python.\n  Use when running fluid dynamics simulations including Navier-Stokes equations (2D\u002F3D),\n  shallow water equations, stratified flows, or when analyzing turbulence, vortex\n  dynamics, or geophysical flows. Provides pseudospectral methods with FFT, HPC support,\n  and comprehensive output analysis.\napp: science\nrequires_approval: true\nagents:\n- '*'\ninputs: []\nexpected_state:\n  description: Imported skill — behavior matches source repo\n  verification_tool: none\nconfidence: 1.0\nattempts: 0\nsuccesses: 0\nlast_adjusted: '2026-05-11T21:21:44+00:00'\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 pip install fluidsim\n\n# With FFT support (required for most solvers)\nuv pip install \"fluidsim[fft]\"\n\n# With MPI for parallel computing\nuv 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\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 pip install fluidsim\n\n# With FFT support (required for most solvers)\nuv pip install \"fluidsim[fft]\"\n\n# With MPI for parallel computing\nuv 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\n",{"app":20,"name":5,"agents":49,"inputs":51,"attempts":52,"successes":52,"confidence":14,"description":7,"last_adjusted":53,"expected_state":54,"requires_approval":57},[50],"*",[],0,"2026-05-11T21:21:44+00:00",{"description":55,"verification_tool":56},"Imported skill — behavior matches source repo","none",true,"master","5f13b5d2b532c0ab6f847e3aa24d4bfe66f7d461","skills\u002Fscience\u002Ffluidsim","https:\u002F\u002Fgithub.com\u002FFlissel\u002Fvibemind-os","https:\u002F\u002Fgithub.com\u002FFlissel","https:\u002F\u002Fvibemind.space","Co-founder & CTO, VibeMind - a voice-first agentic OS for non-technical founders. 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