fluidsim

fluidsim is a skill for Claude Code, Codex from crazymsn/academic-skills. It costs 69 tokens per session (2,512 once invoked), scanned A, a copy of fluidsim, MIT.

A Python framework for running computer simulations of moving fluids, such as air or water. It includes models for fluid equations, shallow water, layered flows, and turbulence.

In plain words
What is it for?
Use it to run two- or three-dimensional fluid simulations, including water-flow, atmospheric, geophysical, and vortex studies. It also supports analyzing and visualizing simulation results.
Why use it?
It brings simulation setup, execution, speed improvements, and result analysis into one Python workflow. This reduces the need to build separate tools for each stage of a fluid study.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to run two- or three-dimensional fluid simulations, including water-flow, atmospheric, geophysical, and vortex studies. It also supports analyzing and visualizing simulation results.

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Install with agentmods
npx agentmods add skills/crazymsn/academic-skills/fluidsim
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add crazymsn/academic-skills --skill fluidsim
Clone the repo
git clone --depth 1 https://github.com/crazymsn/academic-skills

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for fluidsim

README.md
[![agentmods](https://agentmods.dev/badge/skills/crazymsn/academic-skills/fluidsim.svg)](https://agentmods.dev/skills/crazymsn/academic-skills/fluidsim)
Your own site
<a href="https://agentmods.dev/skills/crazymsn/academic-skills/fluidsim"><img src="https://agentmods.dev/badge/skills/crazymsn/academic-skills/fluidsim.svg" alt="Measured on agentmods" height="20"></a>
Per session 69 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 2,512 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
Origin 88% copy Near-identical to another mod in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00069 $0.02512
Opus 5 $0.00034 $0.01256
Sonnet 5 $0.00014 $0.00502
Haiku 4.5 $0.00007 $0.00251

Measured 8d ago against content hash 2c271bcc0872, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

fluidsim scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 8d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

Origin

This is a copy

88% identical to fluidsim — 13 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.

academic-skills/fluidsim/SKILL.md · 346 lines

How it starts

The opening of the file, as written. The whole thing — 346 lines — stays where its author put it; the contents beside it link to each section on GitHub.

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.

Read the full file on GitHub · 346 lines

Files

What ships with it

6 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 8d ago First seen · 346 lines · 69 tokens per session scan A 2c271bcc0872

Subscribe to this mod's changes

fluidsim is a skill published in the GitHub repository crazymsn/academic-skills (22 stars, last pushed 3mo ago), licensed MIT. It adds 69 tokens to every session and 2,512 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 88% identical to fluidsim, differing in 13 lines, and is treated as a copy.

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