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FluidSim CFD Simulation Guardrails

A rigorous workflow skill for planning, validating, restarting, and analyzing FluidSim 0.9 pseudospectral CFD runs with explicit numerical and HPC safety gates.

Data & AnalyticsAdvanced★ 33,030⑂ 3,248AI score 8/10Last updated: Aug 9, 2026

What it does

  • Guides solver selection across FluidSim 0.9.0 (ns2d, ns3d, Boussinesq and stratified variants) and forces inspection of generated default parameters before editing.
  • Builds a strict JSON plan with hard bounds on CPU, RAM, disk, wall-time, CFL, resolution and dealiasing, then checks it with bundled solver_config_validator.py and grid_resource_estimator.py.
  • Enforces the order: dry-run script → tiny serial pilot → independent grid and timestep refinement → only then a site-specific MPI job, and never auto-submits MPI.
  • Ships read-only analysis tools for output inventory, energy budgets and restart compatibility, and refuses the upstream --modify-params option that executes arbitrary Python.
  • Explicitly rejects "it finished and the plot looks smooth" as evidence of convergence, demanding spectra, CFL history, and conservation residuals.

Who it's for

  • Graduate students and researchers doing periodic pseudospectral CFD.
  • Computational scientists wiring FFTW/PFFT/P3DFFT backends on HPC clusters.
  • Teams that must keep reproducible provenance: lockfiles, checksums, restart lineage.

Examples

  1. "Run a forced 2D turbulence ns2d case at 512²" — the skill first pins equations, units and acceptance criteria, then emits a validated config plus a resource estimate.
  2. "Can I trust the results in this run directory?" — output_inventory.py and budget_summary.py audit files and energy-budget residuals.
  3. "Restart from the last checkpoint with tweaked forcing" — restart_compatibility.py compares solver, grid, state variables and versions before anything runs.

· · · Install guide · · ·

Try it now, no install

Paste this into Claude to use the skill without installing anything.

Read the instructions in this file and follow them to help me:
https://raw.githubusercontent.com/K-Dense-AI/scientific-agent-skills/HEAD/skills/fluidsim/SKILL.md

What I want: (describe your task here)

If Claude can't open the link, open it yourself and paste the contents instead.

↓ If it works for you, download the ZIP below and install it. Then it runs on its own — no pasting each time.

Install in the Claude app (no terminal)
  1. Download the ZIP with the button below.
  2. In Claude, open Settings → Capabilities and turn on 'Code execution and file creation'. (one time)
  3. Go to Customize → Skills → + → 'Upload a skill' and upload the ZIP.
↓ Download ZIP
Install in Claude Code

Let Claude do it — paste this into Claude Code

Install the skill I found on AI Skill Mart.
Copy the skills/fluidsim folder from the GitHub repo K-Dense-AI/scientific-agent-skills into my ~/.claude/skills/fluidsim/.
When it's done, tell me in one line what this skill can do.

Install with a command instead

git clone https://github.com/K-Dense-AI/scientific-agent-skills.git && mkdir -p ~/.claude/skills && cp -r scientific-agent-skills/skills/fluidsim ~/.claude/skills/

⚠ This is a third-party skill. Check the source repository before installing.

  1. Open a terminal and create the skills folder: mkdir -p ~/.claude/skills
  2. Clone the repository: git clone https://github.com/K-Dense-AI/scientific-agent-skills.git
  3. Copy just this skill: cp -r scientific-agent-skills/skills/fluidsim ~/.claude/skills/
  4. Confirm Python 3.11+ is available: python3 --version
  5. For real simulations, create an isolated env: uv venv --python 3.11 && uv pip install "fluidsim[fft]==0.9.0" "fluidfft==0.4.5" "pyFFTW==0.15.1"
  6. Restart Claude Code and prompt something like "review my ns2d FluidSim configuration" to trigger the skill.
  7. For MPI or native FFT backends, have your cluster admin install a compatible MPI runtime and FFTW development headers first.
View source on GitHub ↗License: MIT