How do I install fluidsim?

Run `npx skills add https://github.com/K-Dense-AI/scientific-agent-skills --skill fluidsim` in your terminal. You need to have run `npx skills init` once in your project first.

Which agent frameworks does fluidsim support?

fluidsim works with any agent framework supported by the Skills registry, including Claude Code, Cursor, GitHub Copilot, Cline, Codex, and Gemini CLI.

Is fluidsim free to use?

Yes. fluidsim is free to install and use. It is available from the open explainx.ai skill registry published by K-Dense-AI.

Where can I read ratings and reviews for fluidsim?

Community ratings and review text appear on this explainx.ai skill page below the description. Reviews use a 1–5 scale and may include short written feedback from signed-in members.

How do I install fluidsim?

Run `npx skills add https://github.com/K-Dense-AI/scientific-agent-skills --skill fluidsim` in your terminal. You need to have run `npx skills init` once in your project first.

Which agent frameworks does fluidsim support?

fluidsim works with any agent framework supported by the Skills registry, including Claude Code, Cursor, GitHub Copilot, Cline, Codex, and Gemini CLI.

Is fluidsim free to use?

Yes. fluidsim is free to install and use. It is available from the open explainx.ai skill registry published by K-Dense-AI.

Where can I read ratings and reviews for fluidsim?

Community ratings and review text appear on this explainx.ai skill page below the description. Reviews use a 1–5 scale and may include short written feedback from signed-in members.

How do I install fluidsim?

Run `npx skills add https://github.com/K-Dense-AI/scientific-agent-skills --skill fluidsim` in your terminal. You need to have run `npx skills init` once in your project first.

Which agent frameworks does fluidsim support?

fluidsim works with any agent framework supported by the Skills registry, including Claude Code, Cursor, GitHub Copilot, Cline, Codex, and Gemini CLI.

Is fluidsim free to use?

Yes. fluidsim is free to install and use. It is available from the open explainx.ai skill registry published by K-Dense-AI.

Where can I read ratings and reviews for fluidsim?

Community ratings and review text appear on this explainx.ai skill page below the description. Reviews use a 1–5 scale and may include short written feedback from signed-in members.

How do I install fluidsim?

Run `npx skills add https://github.com/K-Dense-AI/scientific-agent-skills --skill fluidsim` in your terminal. You need to have run `npx skills init` once in your project first.

Which agent frameworks does fluidsim support?

fluidsim works with any agent framework supported by the Skills registry, including Claude Code, Cursor, GitHub Copilot, Cline, Codex, and Gemini CLI.

Is fluidsim free to use?

Yes. fluidsim is free to install and use. It is available from the open explainx.ai skill registry published by K-Dense-AI.

Where can I read ratings and reviews for fluidsim?

Community ratings and review text appear on this explainx.ai skill page below the description. Reviews use a 1–5 scale and may include short written feedback from signed-in members.

How do I install fluidsim?

Run `npx skills add https://github.com/K-Dense-AI/scientific-agent-skills --skill fluidsim` in your terminal. You need to have run `npx skills init` once in your project first.

Which agent frameworks does fluidsim support?

fluidsim works with any agent framework supported by the Skills registry, including Claude Code, Cursor, GitHub Copilot, Cline, Codex, and Gemini CLI.

Is fluidsim free to use?

Yes. fluidsim is free to install and use. It is available from the open explainx.ai skill registry published by K-Dense-AI.

Where can I read ratings and reviews for fluidsim?

Community ratings and review text appear on this explainx.ai skill page below the description. Reviews use a 1–5 scale and may include short written feedback from signed-in members.

How do I install fluidsim?

Run `npx skills add https://github.com/K-Dense-AI/scientific-agent-skills --skill fluidsim` in your terminal. You need to have run `npx skills init` once in your project first.

Which agent frameworks does fluidsim support?

fluidsim works with any agent framework supported by the Skills registry, including Claude Code, Cursor, GitHub Copilot, Cline, Codex, and Gemini CLI.

Is fluidsim free to use?

Yes. fluidsim is free to install and use. It is available from the open explainx.ai skill registry published by K-Dense-AI.

Where can I read ratings and reviews for fluidsim?

Community ratings and review text appear on this explainx.ai skill page below the description. Reviews use a 1–5 scale and may include short written feedback from signed-in members.

How do I install fluidsim?

Run `npx skills add https://github.com/K-Dense-AI/scientific-agent-skills --skill fluidsim` in your terminal. You need to have run `npx skills init` once in your project first.

Which agent frameworks does fluidsim support?

fluidsim works with any agent framework supported by the Skills registry, including Claude Code, Cursor, GitHub Copilot, Cline, Codex, and Gemini CLI.

Is fluidsim free to use?

Yes. fluidsim is free to install and use. It is available from the open explainx.ai skill registry published by K-Dense-AI.

Where can I read ratings and reviews for fluidsim?

Community ratings and review text appear on this explainx.ai skill page below the description. Reviews use a 1–5 scale and may include short written feedback from signed-in members.

How do I install fluidsim?

Run `npx skills add https://github.com/K-Dense-AI/scientific-agent-skills --skill fluidsim` in your terminal. You need to have run `npx skills init` once in your project first.

Which agent frameworks does fluidsim support?

fluidsim works with any agent framework supported by the Skills registry, including Claude Code, Cursor, GitHub Copilot, Cline, Codex, and Gemini CLI.

Is fluidsim free to use?

Yes. fluidsim is free to install and use. It is available from the open explainx.ai skill registry published by K-Dense-AI.

Where can I read ratings and reviews for fluidsim?

Community ratings and review text appear on this explainx.ai skill page below the description. Reviews use a 1–5 scale and may include short written feedback from signed-in members.

How do I install fluidsim?

Run `npx skills add https://github.com/K-Dense-AI/scientific-agent-skills --skill fluidsim` in your terminal. You need to have run `npx skills init` once in your project first.

Which agent frameworks does fluidsim support?

fluidsim works with any agent framework supported by the Skills registry, including Claude Code, Cursor, GitHub Copilot, Cline, Codex, and Gemini CLI.

Is fluidsim free to use?

Yes. fluidsim is free to install and use. It is available from the open explainx.ai skill registry published by K-Dense-AI.

Where can I read ratings and reviews for fluidsim?

Community ratings and review text appear on this explainx.ai skill page below the description. Reviews use a 1–5 scale and may include short written feedback from signed-in members.

How do I install fluidsim?

Run `npx skills add https://github.com/K-Dense-AI/scientific-agent-skills --skill fluidsim` in your terminal. You need to have run `npx skills init` once in your project first.

Which agent frameworks does fluidsim support?

fluidsim works with any agent framework supported by the Skills registry, including Claude Code, Cursor, GitHub Copilot, Cline, Codex, and Gemini CLI.

Is fluidsim free to use?

Yes. fluidsim is free to install and use. It is available from the open explainx.ai skill registry published by K-Dense-AI.

Where can I read ratings and reviews for fluidsim?

Community ratings and review text appear on this explainx.ai skill page below the description. Reviews use a 1–5 scale and may include short written feedback from signed-in members.

How do I install fluidsim?

Run `npx skills add https://github.com/K-Dense-AI/scientific-agent-skills --skill fluidsim` in your terminal. You need to have run `npx skills init` once in your project first.

Science

fluidsim▌

K-Dense-AI/scientific-agent-skills · updated Jun 4, 2026

MDX-style export adds YAML metadata + attribution linking explainx.ai and this canonical listing URL.

$npx skills add https://github.com/K-Dense-AI/scientific-agent-skills --skill fluidsim

0 commentsdiscussion

summary

### Fluidsim

›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, o..."

skill.md

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.
license	CeCILL FREE SOFTWARE LICENSE AGREEMENT
metadata	version: "1.0" skill-author: K-Dense Inc.

FluidSim

Overview

FluidSim 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/C++ while maintaining Python's ease of use.

Key strengths:

Multiple solvers: 2D/3D Navier-Stokes, shallow water, stratified flows
High performance: Pythran/Transonic compilation, MPI parallelization
Complete workflow: Parameter configuration, simulation execution, output analysis
Interactive analysis: Python-based post-processing and visualization

Core Capabilities

1. Installation and Setup

Install fluidsim using uv with appropriate feature flags:

# Basic installation
uv pip install fluidsim

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

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

Set environment variables for output directories (optional):

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

No API keys or authentication required.

See references/installation.md for complete installation instructions and environment configuration.

2. Running Simulations

Standard workflow consists of five steps:

Step 1: Import solver

from fluidsim.solvers.ns2d.solver import Simul

Step 2: Create and configure parameters

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"

Step 3: Instantiate simulation

sim = Simul(params)

Step 4: Execute

sim.time_stepping.start()

Step 5: Analyze results

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

See references/simulation_workflow.md for complete examples, restarting simulations, and cluster deployment.

3. Available Solvers

Choose solver based on physical problem:

2D Navier-Stokes (ns2d): 2D turbulence, vortex dynamics

from fluidsim.solvers.ns2d.solver import Simul

3D Navier-Stokes (ns3d): 3D turbulence, realistic flows

from fluidsim.solvers.ns3d.solver import Simul

Stratified flows (ns2d.strat, ns3d.strat): Oceanic/atmospheric flows

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

Shallow water (sw1l): Geophysical flows, rotating systems

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

See references/solvers.md for complete solver list and selection guidance.

4. Parameter Configuration

Parameters are organized hierarchically and accessed via dot notation:

Domain and resolution:

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

Physical parameters:

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

Time stepping:

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

Initial conditions:

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

Output settings:

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

The Parameters object raises AttributeError for typos, preventing silent configuration errors.

See references/parameters.md for comprehensive parameter documentation.

5. Output and Analysis

FluidSim produces multiple output types automatically saved during simulation:

Physical fields: Velocity, vorticity in HDF5 format

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

Spatial means: Time series of volume-averaged quantities

sim.output.spatial_means.plot()

Spectra: Energy and enstrophy spectra

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

Load previous simulations:

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

Advanced visualization: Open .h5 files in ParaView or VisIt for 3D visualization.

See references/output_analysis.md for detailed analysis workflows, parametric study analysis, and data export.

6. Advanced Features

Custom forcing: Maintain turbulence or drive specific dynamics

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

Custom initial conditions: Define fields in script

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()

MPI parallelization: Run on multiple processors

mpirun -np 8 python simulation_script.py

Parametric studies: Run multiple simulations with different parameters

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()

See references/advanced_features.md for forcing types, custom solvers, cluster submission, and performance optimization.

Common Use Cases

2D Turbulence Study

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)

Stratified Flow Simulation

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")

High-Resolution 3D Simulation with MPI

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()

Run with:

mpirun -np 64 python script.py

Taylor-Green Vortex Validation

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

Quick Reference

Import solver: from fluidsim.solvers.ns2d.solver import Simul

Create parameters: params = Simul.create_default_params()

Set resolution: params.oper.nx = params.oper.ny = 256

Set viscosity: params.nu_2 = 1e-3

Set end time: params.time_stepping.t_end = 10.0

Run simulation: sim = Simul(params); sim.time_stepping.start()

Plot results: sim.output.phys_fields.plot("vorticity")

Load simulation: sim = load_sim_for_plot("path/to/sim")

Resources

Documentation: https://fluidsim.readthedocs.io/

Reference files:

references/installation.md: Complete installation instructions
references/solvers.md: Available solvers and selection guide
references/simulation_workflow.md: Detailed workflow examples
references/parameters.md: Comprehensive parameter documentation
references/output_analysis.md: Output types and analysis methods
references/advanced_features.md: Forcing, MPI, parametric studies, custom solvers

how to use fluidsim

How to use fluidsim on Cursor

AI-first code editor with Composer

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

›Cursor installed and configured on your development machine
›Node.js version 16.0+ with npm package manager (verify with node --version)
›Active project directory or workspace where you want to add fluidsim

Execute installation command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/K-Dense-AI/scientific-agent-skills --skill fluidsim

The skills CLI fetches fluidsim from GitHub repository K-Dense-AI/scientific-agent-skills and configures it for Cursor.

Select Cursor when prompted

The CLI will show a list of available agents. Use arrow keys to navigate and space to select Cursor:

◆ Which agents do you want to install to?

│

│ ── Universal (.agents/skills) ── always included ────

│ • Amp

│ • Antigravity

│ • Cline

│ • Codex

│ ●Cursor(selected)

│ • Cursor

│ • Windsurf

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/fluidsim

Reload or restart Cursor to activate fluidsim. Access the skill through slash commands (e.g., /fluidsim) or your agent's skill management interface.

⚠

Security & Verification Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your development environment. Always verify the publisher's identity, review recent commits, and test in isolated environments before production deployment.

Additional Resources

›View source code on GitHub ›Skills CLI documentation ›Learn more about Cursor ›What are agent skills?

List & Monetize Your Skill

Submit your Claude Code skill and start earning

GET_STARTED →

Use Cases▌

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

✓

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

✓

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

✓

Improve work quality by 30-40% with less effort

Implementation Guide▌

Prerequisites

›Claude Desktop or compatible AI client with skill support
›Clear understanding of task or problem to solve
›Willingness to iterate and refine outputs

Time Estimate

15-45 minutes depending on use case complexity

Installation Steps

1.Install skill using provided installation command
2.Test with simple use case relevant to your work
3.Evaluate output quality and relevance
4.Iterate on prompts to improve results
5.Integrate into regular workflow if valuable

Common Pitfalls

⚠Expecting perfect results without iteration
⚠Not providing enough context in prompts
⚠Using skill for tasks outside its intended scope
⚠Accepting outputs without review and validation

Best Practices▌

✓ Do

+Start with clear, specific prompts
+Provide relevant context and constraints
+Review and refine all outputs before using
+Iterate to improve output quality
+Document successful prompt patterns

✗ Don't

−Don't use without understanding skill limitations
−Don't skip validation of outputs
−Don't share sensitive information in prompts
−Don't expect skill to replace human judgment

💡 Pro Tips

★Be specific about desired format and style
★Ask for multiple options to choose from
★Request explanations to understand reasoning
★Combine AI efficiency with human expertise

When to Use This▌

✓ Use When

Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.

✗ Avoid When

Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.

Learning Path▌

1Familiarize yourself with skill capabilities and limitations
2Start with low-risk, non-critical tasks
3Progress to more complex and valuable use cases
4Build expertise through regular use and experimentation

Discussion

Product Hunt–style comments (not star reviews)

No comments yet — start the thread.

general reviews

Ratings

4.6★★★★★43 reviews

★★★★★Sakura Martin· Dec 24, 2024
Registry listing for fluidsim matched our evaluation — installs cleanly and behaves as described in the markdown.
★★★★★Ren Liu· Dec 20, 2024
Useful defaults in fluidsim — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
★★★★★Sakura Brown· Dec 16, 2024
I recommend fluidsim for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
★★★★★Shikha Mishra· Dec 12, 2024
fluidsim fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
★★★★★Olivia Lopez· Dec 4, 2024
fluidsim fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
★★★★★Sakura Taylor· Nov 15, 2024
Useful defaults in fluidsim — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
★★★★★Sakura Lopez· Nov 11, 2024
Registry listing for fluidsim matched our evaluation — installs cleanly and behaves as described in the markdown.
★★★★★Noah Choi· Nov 7, 2024
fluidsim reduced setup friction for our internal harness; good balance of opinion and flexibility.
★★★★★Noah Perez· Oct 26, 2024
Registry listing for fluidsim matched our evaluation — installs cleanly and behaves as described in the markdown.
★★★★★Li Thomas· Oct 6, 2024
I recommend fluidsim for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.

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