FluidSim CFD Simulations

What it does

When your agent uses it

• Setting up a 2D turbulence run with the Navier-Stokes solver
• Simulating stratified or shallow-water flows for geophysical studies
• Plotting vorticity and spatial means from a finished simulation
• Restarting a simulation or moving it to a cluster

Example prompts

• “Set up a 2D Navier-Stokes simulation on a 256 by 256 grid and plot the vorticity at the end.”
• “Configure a stratified 3D flow with a Brunt-Vaisala frequency of 1 and write outputs to my scratch folder.”
• “Show me how to restart yesterday's fluidsim run from its last saved state.”

Requirements

• Python with `fluidsim` installed
• MPI and Pythran or Transonic for faster parallel runs (optional)

Workflow steps

6 steps, taken from the step headings in SKILL.md.

1. 1Installation and Setup
2. 2Running Simulations
3. 3Available Solvers
4. 4Parameter Configuration
5. 5Output and Analysis
6. 6Advanced Features

What it can do on your machine

Read from SKILL.md and the folder at commit 14680ec. It shows what the files ask for, not the result of running them.

• Tool permissions

  Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

  From allowed-tools in the SKILL.md frontmatter.

• Runs code

  Shell commands in SKILL.md call:

  • uv

  From the folder's file list and the shell code blocks in SKILL.md.

• Network

  Links to these hosts (documentation or services it may open):

  • fluidsim.readthedocs.io

  From URLs in SKILL.md, links to its own repository left out.

• Credentials

  Names no API keys, tokens, secrets or passwords.

  From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

FluidSim CFD Simulations loads about 2.3k tokens when it runs, and up to ~9.2k if it reads all its reference files. Until then it costs about 92 tokens; SKILL.md has 424 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it

~92

When it runs · the whole SKILL.md, loaded when a task matches

~2.3k

With references · SKILL.md plus every file in references/, read only if the agent opens them

~9.2k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from davila7/claude-code-templates at commit 14680ec, republished under its MIT licence (© davila7). 424 words, ~2,326 tokens.

name

fluidsim

description

Framework for computational fluid dynamics simulations using Python. Use when running fluid dynamics simulations including Navier-Stokes equations (2D/3D), 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.

# Basic installation
uv uv pip install fluidsim

# With FFT support (required for most solvers)
uv uv pip install "fluidsim[fft]"

# With MPI for parallel computing
uv uv pip install "fluidsim[fft,mpi]"

export FLUIDSIM_PATH=/path/to/simulation/outputs
export FLUIDDYN_PATH_SCRATCH=/path/to/working/directory

from fluidsim.solvers.ns2d.solver import Simul

params = Simul.create_default_params()
params.oper.nx = params.oper.ny = 256
params.oper.Lx = params.oper.Ly = 2 * 3.14159
params.nu_2 = 1e-3
params.time_stepping.t_end = 10.0
params.init_fields.type = "noise"

sim = Simul(params)

sim.time_stepping.start()

sim.output.phys_fields.plot("vorticity")
sim.output.spatial_means.plot()

from fluidsim.solvers.ns2d.solver import Simul

from fluidsim.solvers.ns3d.solver import Simul

from fluidsim.solvers.ns2d.strat.solver import Simul
params.N = 1.0  # Brunt-Väisälä frequency

from fluidsim.solvers.sw1l.solver import Simul
params.f = 1.0  # Coriolis parameter

params.oper.nx = 256  # grid points
params.oper.Lx = 2 * pi  # domain size

params.nu_2 = 1e-3  # viscosity
params.nu_4 = 0     # hyperviscosity (optional)

params.time_stepping.t_end = 10.0
params.time_stepping.USE_CFL = True  # adaptive time step
params.time_stepping.CFL = 0.5

params.init_fields.type = "noise"  # or "dipole", "vortex", "from_file", "in_script"

params.output.periods_save.phys_fields = 1.0  # save every 1.0 time units
params.output.periods_save.spectra = 0.5
params.output.periods_save.spatial_means = 0.1

sim.output.phys_fields.plot("vorticity")
sim.output.phys_fields.plot("vx")

sim.output.spatial_means.plot()

sim.output.spectra.plot1d()
sim.output.spectra.plot2d()

from fluidsim import load_sim_for_plot
sim = load_sim_for_plot("simulation_dir")
sim.output.phys_fields.plot()

params.forcing.enable = True
params.forcing.type = "tcrandom"  # time-correlated random forcing
params.forcing.forcing_rate = 1.0

params.init_fields.type = "in_script"
sim = Simul(params)
X, Y = sim.oper.get_XY_loc()
vx = sim.state.state_phys.get_var("vx")
vx[:] = sin(X) * cos(Y)
sim.time_stepping.start()

mpirun -np 8 python simulation_script.py

for nu in [1e-3, 5e-4, 1e-4]:
    params = Simul.create_default_params()
    params.nu_2 = nu
    params.output.sub_directory = f"nu{nu}"
    sim = Simul(params)
    sim.time_stepping.start()

from fluidsim.solvers.ns2d.solver import Simul
from math import pi

params = Simul.create_default_params()
params.oper.nx = params.oper.ny = 512
params.oper.Lx = params.oper.Ly = 2 * pi
params.nu_2 = 1e-4
params.time_stepping.t_end = 50.0
params.time_stepping.USE_CFL = True
params.init_fields.type = "noise"
params.output.periods_save.phys_fields = 5.0
params.output.periods_save.spectra = 1.0

sim = Simul(params)
sim.time_stepping.start()

# Analyze energy cascade
sim.output.spectra.plot1d(tmin=30.0, tmax=50.0)

from fluidsim.solvers.ns2d.strat.solver import Simul

params = Simul.create_default_params()
params.oper.nx = params.oper.ny = 256
params.N = 2.0  # stratification strength
params.nu_2 = 5e-4
params.time_stepping.t_end = 20.0

# Initialize with dense layer
params.init_fields.type = "in_script"
sim = Simul(params)
X, Y = sim.oper.get_XY_loc()
b = sim.state.state_phys.get_var("b")
b[:] = exp(-((X - 3.14)**2 + (Y - 3.14)**2) / 0.5)
sim.state.statephys_from_statespect()

sim.time_stepping.start()
sim.output.phys_fields.plot("b")

from fluidsim.solvers.ns3d.solver import Simul

params = Simul.create_default_params()
params.oper.nx = params.oper.ny = params.oper.nz = 512
params.nu_2 = 1e-5
params.time_stepping.t_end = 10.0
params.init_fields.type = "noise"

sim = Simul(params)
sim.time_stepping.start()

mpirun -np 64 python script.py

from fluidsim.solvers.ns2d.solver import Simul
import numpy as np
from math import pi

params = Simul.create_default_params()
params.oper.nx = params.oper.ny = 128
params.oper.Lx = params.oper.Ly = 2 * pi
params.nu_2 = 1e-3
params.time_stepping.t_end = 10.0
params.init_fields.type = "in_script"

sim = Simul(params)
X, Y = sim.oper.get_XY_loc()
vx = sim.state.state_phys.get_var("vx")
vy = sim.state.state_phys.get_var("vy")
vx[:] = np.sin(X) * np.cos(Y)
vy[:] = -np.cos(X) * np.sin(Y)
sim.state.statephys_from_statespect()

sim.time_stepping.start()

# Validate energy decay
df = sim.output.spatial_means.load()
# Compare with analytical solution

© davila7, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 6 other files (references) in cli-tool/components/skills/scientific/fluidsim of davila7/claude-code-templates.

• SKILL.md
• references/advanced_features.md
• references/installation.md
• references/output_analysis.md
• references/parameters.md
• references/simulation_workflow.md
• references/solvers.md

Open the folder on GitHubat commit 14680ec

Used in 10 other repositories

We found 25 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 10 other GitHub owners. This page covers the copy in davila7/claude-code-templates, which our catalogue first saw on October 7, 2026.

• jimmc414/Kosmoskosmos-claude-scientific-skills/scientific-skills/fluidsim
• Microck/ordinary-claude-skillsskills_all/fluidsimskills_categorized/astronomy-physics/fluidsim+2 more
• aiskillstore/marketplaceskills/davila7/fluidsimskills/k-dense-ai/fluidsim
• majiayu000/claude-skill-registryskills/ai-ml/fluidsimskills/analysis/scientific-fluidsim+10 more
• lamm-mit/scienceclawskills/fluidsim
• agent-skills-hub/agent-skills-hubskills/fluidsim
• foryourhealth111-pixel/Vibe-Skillsbundled/skills/fluidsim
• LeonChaoX/qinyan-academic-skillsskills/10-材料科学与物理计算/fluidsim
• BioTender-max/awesome-bio-agent-skillsskills/kdense/fluidsim
• infometa/workbuddyskillsplugins/codebuddy-plugins-official/external_plugins/scientific-skills/fluidsim