K-Dense-AI/scientific-agent-skills/skills/fluidsim/SKILL.md
fluidsim
Plan, configure, inspect, restart, and analyze bounded FluidSim computational-fluid-dynamics simulations with explicit numerical-validity and HPC safety checks. Use for FluidSim solver selection, parameter review, FFT/MPI setup, output diagnostics, or restart compatibility.
- Source repository stars
- 31,966
- Declared platforms
- 0
- Static risk flags
- 1
- Last source update
- 2026-07-28
- Source checked
- 2026-07-28
Decision brief
What it does—and where it fits
Use FluidSim 0.9.0 as a framework for Python-defined numerical solvers, especially periodic Cartesian pseudospectral CFD. Upstream FluidSim is CeCILL-2.1; the MIT frontmatter license applies only to this skill.
Not for
- Tasks that require unconfirmed production actions or broad system permissions.
- Environments where the pinned source and install steps cannot be inspected.
Compatibility matrix
Platform support, with evidence labels
| Platform | Status | Evidence | What to check |
|---|---|---|---|
| Codex | Not declared | No explicit evidence | Portability before use |
| Claude Code | Not declared | No explicit evidence | Portability before use |
| Cursor | Not declared | No explicit evidence | Portability before use |
| Gemini CLI | Not declared | No explicit evidence | Portability before use |
Installation
Inspect first. Install second.
The source command is displayed only when detected. A safe inspection prompt is always available so your agent can explain every action before execution.
npx skills add https://github.com/K-Dense-AI/scientific-agent-skills --skill "skills/fluidsim"Inspect the Agent Skill "fluidsim" from https://github.com/K-Dense-AI/scientific-agent-skills/blob/e7ac42510774624f327003c95b6650e2883bc01d/skills/fluidsim/SKILL.md at commit e7ac42510774624f327003c95b6650e2883bc01d. List every install step, command, network request, credential, file read/write, external action, and rollback step. Explain whether it fits my task. Do not install or execute anything until I approve.
Workflow
What the source asks the agent to do
- 01
Required workflow
1. State equations, units or nondimensionalization, geometry, boundaries, initial conditions, forcing, observables, and acceptance criteria. 2. Select a verified solver and inspect its generated default parameters. 3. Create a strict JSON plan with explicit CPU, RAM, disk, wall-…
State equations, units or nondimensionalization, geometry, boundaries,Select a verified solver and inspect its generated default parameters.Create a strict JSON plan with explicit CPU, RAM, disk, wall-time, output-file, - 02
Version and installation
As verified on 2026-07-23:
Latest stable PyPI release: fluidsim==0.9.0 (2025-12-04).Package metadata requires Python =3.11 and lists Python 3.11–3.14.Pseudospectral parameter creation needs FluidFFT; bare fluidsim imported in - 03
API snapshot
Use direct, versioned imports:
CFL field: params.timestepping.cflcoef, not CFL.Time-correlated forcing:NS2D default initial types include constant, noise, jet, dipole, - 04
Solvers
Primary Cartesian CFD keys and imports:
Primary Cartesian CFD keys and imports:The 0.9 registry also includes plate2d, sw1l variants, waves2d, 1D models, 0D models, spherical solvers, and framework adapters. Availability in the registry does not make a solver appropriate for a scientific question.… - 05
Forcing and time advancement
Forcing is solver-specific. A current normalized random example is:
Forcing is solver-specific. A current normalized random example is:Record the forced variable, normalization definition, wave-number band, random seed/state, injection target, and measured injection. FluidSim 0.9 saves state parameters for restart; 0.8.6 fixed time-correlated forcing r…Available pseudospectral schemes include Euler/RK2 phase-shift variants, RK2trapezoid, and RK4. A named order does not establish accuracy. Check CFL, fast-wave/diffusive limits, deltatmax, and time-step refinement. See…
Permission review
Static risk signals and limitations
Runs scripts
The documentation asks the agent to run terminal commands or scripts.
Generate and review a dry-run script. It does nothing unless executed with anRuns scripts
The documentation asks the agent to run terminal commands or scripts.
python3 scripts/solver_config_validator.py --exampleEvidence record
Why each signal appears
| Signal | Value | Evidence type | Meaning |
|---|---|---|---|
| Quality score | 93/100 | Computed | Documentation, specificity, maintenance, and trust rules |
| Repository stars | 31,966 | Source | Repository attention, not individual Skill quality |
| Compatibility | 0 platforms | Source | Declared in the catalog source record |
| Usage guide | automated source guide | Editorial | Generated or reviewed according to the visible evidence level |
Pinned source
Provenance and original SKILL.md
- Repository
- K-Dense-AI/scientific-agent-skills
- Skill path
- skills/fluidsim/SKILL.md
- Commit
- e7ac42510774624f327003c95b6650e2883bc01d
- License
- MIT
- Collected
- 2026-07-28
- Default branch
- main
View the original SKILL.md
FluidSim
Use FluidSim 0.9.0 as a framework for Python-defined numerical solvers, especially periodic Cartesian pseudospectral CFD. Upstream FluidSim is CeCILL-2.1; the MIT frontmatter license applies only to this skill.
This skill does not treat a completed run, a stable time step, a smooth plot, or a closed program exit as evidence of numerical convergence or physical validity.
Required workflow
- State equations, units or nondimensionalization, geometry, boundaries, initial conditions, forcing, observables, and acceptance criteria.
- Select a verified solver and inspect its generated default parameters.
- Create a strict JSON plan with explicit CPU, RAM, disk, wall-time, output-file, timestep, CFL, resolution, and dealiasing bounds.
- Run the bundled validator and resource estimator.
- Generate and review a dry-run script. It does nothing unless executed with an explicit config-ID acknowledgement.
- Run one tiny serial pilot. Inspect budgets, divergence/constraints, spectral tails, CFL/time-step history, and output growth.
- Refine grid and time step independently. Check conservation/budget residuals and observable sensitivity.
- Only then prepare a site-specific MPI job. Never submit or launch MPI automatically.
- Preserve config, script,
uv.lock, package/platform/backend versions, logs, output inventory, checksums, and restart lineage.
Stop if physical assumptions, units, boundary conditions, forcing semantics, resolution criteria, resource limits, or acceptance criteria are missing.
Version and installation
As verified on 2026-07-23:
- Latest stable PyPI release:
fluidsim==0.9.0(2025-12-04). - Package metadata requires Python
>=3.11and lists Python 3.11–3.14. - Pseudospectral parameter creation needs FluidFFT; bare
fluidsimimported in the smoke test, butns2d.create_default_params()failed until thefftextra was installed. - Current companion versions tested here:
fluidfft==0.4.5andpyFFTW==0.15.1.
Prefer a project lock:
uv init --python 3.11
uv add "fluidsim[fft]==0.9.0" "fluidfft==0.4.5" "pyFFTW==0.15.1"
uv lock
uv sync --frozen
For an isolated disposable environment:
uv venv --python 3.11
uv pip install "fluidsim[fft]==0.9.0" "fluidfft==0.4.5" "pyFFTW==0.15.1"
The project lock is the reproducibility record; direct pins alone do not freeze all transitive artifacts. Do not reuse a lock across incompatible platforms or MPI ABIs.
MPI is optional and native:
uv add "mpi4py==4.1.2" "fluidfft-mpi-with-fftw==0.0.1" "fluidfft-fftwmpi==0.0.1"
uv lock
Those packages still require a compatible MPI runtime and FFTW development libraries. The optional native plugins are:
fluidfft-fftw==0.0.1: sequentialfft2d.with_fftw1d,fft2d.with_fftw2d,fft3d.with_fftw3d.fluidfft-mpi-with-fftw==0.0.1: MPIfft2d.mpi_with_fftw1d,fft3d.mpi_with_fftw1d.fluidfft-fftwmpi==0.0.1: MPI-enabled FFTWfft2d.mpi_with_fftwmpi2d,fft3d.mpi_with_fftwmpi3d.fluidfft-p3dfft==0.0.1:fft3d.mpi_with_p3dfft; requires P3DFFT.- FluidFFT also declares PFFT and P3DFFT extras; audit and pin their native stacks for the target cluster.
FluidFFT documents cuFFT historically, but FluidFFT 0.4.5 declares no CUDA extra or installed GPU plugin in its package metadata, and its CUDA installation page is unfinished. Do not claim GPU acceleration or install an unrelated CUDA wheel as a FluidSim backend. Treat GPU work as source-level experimental integration requiring separate validation.
See installation for system dependencies, MPI ABI, HDF5-MPI, backend discovery, and verification.
API snapshot
Use direct, versioned imports:
from fluidsim.solvers.ns2d.solver import Simul
params = Simul.create_default_params()
params.oper.nx = params.oper.ny = 32
params.oper.Lx = params.oper.Ly = 2 * 3.141592653589793
params.oper.coef_dealiasing = 2 / 3
params.time_stepping.USE_CFL = True
params.time_stepping.cfl_coef = 0.5
params.time_stepping.deltat0 = 0.001
params.time_stepping.deltat_max = 0.01
params.time_stepping.t_end = 0.1
params.time_stepping.max_elapsed = "00:05:00"
params.init_fields.type = "noise"
params.init_fields.noise.velo_max = 0.01
params.output.HAS_TO_SAVE = False
params.output.ONLINE_PLOT_OK = False
Important 0.9 corrections:
- CFL field:
params.time_stepping.cfl_coef, notCFL. - Time-correlated forcing:
params.forcing.tcrandom.time_correlation, not a flattcrandom_time_correlation. - NS2D default initial types include
constant,noise,jet,dipole,from_file,from_simul, andin_script; do not invent a universal list for every solver. - Output state files default to
state_phys_t*.nc; spectra usespectra1D.h5/spectra2D.h5; scalar means are solver-dependentspatial_means.txtor JSON-lines. params.output.sub_directoryis relative underFLUIDSIM_PATH.
ParamContainer rejects undeclared attributes. Always generate defaults from the
selected Simul class and inspect them before changing values. See
parameters.
Solvers
Primary Cartesian CFD keys and imports:
from fluidsim.solvers.ns2d.solver import Simul # ns2d
from fluidsim.solvers.ns2d.bouss.solver import Simul # ns2d.bouss
from fluidsim.solvers.ns2d.strat.solver import Simul # ns2d.strat
from fluidsim.solvers.ns3d.solver import Simul # ns3d
from fluidsim.solvers.ns3d.bouss.solver import Simul # ns3d.bouss
from fluidsim.solvers.ns3d.strat.solver import Simul # ns3d.strat
The 0.9 registry also includes plate2d, sw1l variants, waves2d, 1D models,
0D models, spherical solvers, and framework adapters. Availability in the
registry does not make a solver appropriate for a scientific question. Verify
equations, variables, geometry, boundaries, and diagnostics in the solver
source. See solvers.
Forcing and time advancement
Forcing is solver-specific. A current normalized random example is:
params.forcing.enable = True
params.forcing.type = "tcrandom"
params.forcing.forcing_rate = 1.0
params.forcing.nkmin_forcing = 4
params.forcing.nkmax_forcing = 5
params.forcing.tcrandom.time_correlation = "based_on_forcing_rate"
Record the forced variable, normalization definition, wave-number band, random seed/state, injection target, and measured injection. FluidSim 0.9 saves state parameters for restart; 0.8.6 fixed time-correlated forcing restart behavior.
Available pseudospectral schemes include Euler/RK2 phase-shift variants,
RK2_trapezoid, and RK4. A named order does not establish accuracy. Check CFL,
fast-wave/diffusive limits, deltat_max, and time-step refinement. See
advanced features.
Outputs, loading, and restart
For read-only analysis:
from fluidsim import load_sim_for_plot
sim = load_sim_for_plot("run-directory", hide_stdout=True)
sim.output.spatial_means.plot()
sim.output.spectra.plot1d()
sim.output.phys_fields.plot(time=1.0)
load_sim_for_plot uses a coarse operator and disables saving/online plotting.
For a state-bearing object:
from fluidsim import load_state_phys_file
sim = load_state_phys_file("run-directory", t_approx="last")
For a controlled restart, prefer load_for_restart or first run
fluidsim-restart --only-check. Do not use --modify-params with untrusted text:
the upstream CLI executes Python code supplied to that option. This skill's
generator never emits it. Verify solver, grid/domain, state variables, versions,
forcing state, checksum, target time, output destination, and resource bounds.
Resolution changes require the dedicated reviewed workflow, not a silent grid
edit. See simulation workflow and
output analysis.
Scientific acceptance gate
Before interpreting results, require:
- Explicit dimensional units or a complete nondimensionalization map.
- Correct equations, periodic geometry/boundaries, initial state, forcing, and diagnostic definitions.
- Resolution and dealiasing evidence: spectra/tails, resolved gradients, and solver-appropriate small-scale criteria.
- Timestep evidence: CFL history, fastest-wave and dissipative limits, and smaller-step comparison.
- Conservation and budget checks including forcing, dissipation, transfers, and residuals.
- Grid/time refinement with uncertainty or sensitivity for reported observables.
- Comparison to an analytical solution, manufactured solution, benchmark, or independently reproduced result where appropriate.
- Complete provenance and restart lineage.
Never label a run “DNS,” “converged,” “validated,” “steady,” or “physically correct” from parameter values or plots alone.
Bundled local tools
All tools emit strict JSON, reject URLs/traversal/symlinks, enforce hard bounds, use no network or subprocess, and never launch a simulation:
python3 scripts/solver_config_validator.py --example
python3 scripts/solver_config_validator.py --config config.json
python3 scripts/grid_resource_estimator.py --config config.json
python3 scripts/simulation_dry_run.py --config config.json --output run.py
python3 scripts/output_inventory.py --path run-directory
python3 scripts/budget_summary.py --path run-directory
python3 scripts/restart_compatibility.py --source state.nc --target-config config.json
The HDF5 tools lazily require h5py, inspect bounded metadata/hyperslabs, and
never follow external links or load full field arrays.
References
- Installation and FFT/MPI backends
- Solver registry and selection
- Simulation, pilot, and restart workflow
- Verified parameter surface
- Output, plotting, and budget analysis
- Forcing, operators, MPI, and migrations
Dated upstream basis
Verified 2026-07-23 against PyPI 0.9.0, FluidSim 0.9 docs, release notes, official source mirror, FluidFFT 0.4.5 docs, and the primary FluidSim (DOI 10.5334/jors.239) and FluidFFT (DOI 10.5334/jors.238) papers. API claims use official docs/source; method/performance claims in the references are scoped to the cited primary papers and their benchmark setups.
Alternatives
Compare before choosing
K-Dense-AI/scientific-agent-skills
dask
Distributed computing for larger-than-RAM pandas/NumPy workflows. Use when you need to scale existing pandas/NumPy code beyond memory or across clusters. Best for parallel file processing, distributed ML, integration with existing pandas code. For out-of-core analytics on single machine use vaex; for in-memory speed use polars.
K-Dense-AI/scientific-agent-skills
neurokit2
Use NeuroKit2 to build or audit reproducible research workflows for physiological time-series preprocessing, event/interval analysis, multimodal alignment, variability, and complexity. Trigger when code imports neurokit2 or needs its current APIs, schemas, and method-aware validation—not for diagnosis or device validation.
K-Dense-AI/scientific-agent-skills
simpy
Build, inspect, test, and analyze bounded process-based discrete-event simulations with SimPy, including events, resources, interrupts, monitoring, replications, warm-up, and reproducible output analysis.
K-Dense-AI/scientific-agent-skills
pymatgen
Analyze, validate, convert, and transform materials structures and computed materials data with current pymatgen APIs, including local phase diagrams, symmetry sensitivity, electronic-structure I/O, and explicitly bounded Materials Project queries.