Jax Modal Analysis

What it does

When your agent uses it

• Tasks that involve Deep learning

Example prompts

• “/jax-modal-analysis”

Requirements

• Python 3

Workflow steps

2 steps, taken from the first numbered list in SKILL.md.

1. 1Run fem-analysis to shortlist candidates (fast 2D pass/fail)
2. 2Run jax-modal-analysis on shortlisted STLs for full 3D validation

What it can do on your machine

Read from SKILL.md and the folder at commit ab9aba1. 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

  Ships 2 files in scripts/ (Python), which the agent can run.

  Shell commands in SKILL.md call:

  • python3

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

• Network

  No URLs in SKILL.md.

  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

Jax Modal Analysis loads about 811 tokens when it runs. Until then it costs about 119 tokens; SKILL.md has 163 words of instructions outside code blocks.

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

~119

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

~811

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); the scripts in this folder are not scanned.

SKILL.md

The full file from lamm-mit/scienceclaw at commit ab9aba1, republished under its Apache-2.0 licence (© lamm-mit). 163 words, ~811 tokens.

name

jax-modal-analysis

description

3D tetrahedral FEM modal analysis of a membrane STL. Takes a binary STL (mm units) + material properties JSON, repairs surface mesh, generates tetrahedral volume mesh via TetGen, assembles 3D stiffness/mass matrices with jax-fem, solves the generalised eigenvalue problem, and reports eigenfrequencies + mode shapes. Returns artifact JSON with eigenfrequencies_hz, eigenfrequencies_khz, modes_in_range, target_range_pass, and paths to summary PNG and CSV.

metadata.category

materials-design

metadata.requires

stl_modal_pipeline, tetgen, pyvista, meshio, trimesh, scipy, jax

metadata.conda_env

jax_fem

python3 {baseDir}/scripts/jax_modal_analysis.py \
  --stl /path/to/membrane.stl \
  --material '{"E_Pa":3e9,"nu":0.35,"rho_kg_m3":1500}' \
  --num-modes 12 \
  --solver-backend jax-iterative \
  --stl-length-scale 1e-3 \
  --target-freq-min 2000 \
  --target-freq-max 8000 \
  --output-dir /tmp/jax_modal_results

{
  "stl_path": "/path/to/membrane.stl",
  "topology": "v1_cricket_fine",
  "num_modes_computed": 12,
  "eigenfrequencies_hz":  [0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 2153.0, 2388.1, ...],
  "eigenfrequencies_khz": [0.000, 0.000, 0.000, 0.000, 0.000, 0.000, 2.153, 2.388, ...],
  "modes_in_range_hz":  [2153.0, 2388.1, 5401.2, 6890.3],
  "modes_in_range_khz": [2.153, 2.388, 5.401, 6.890],
  "target_range_hz": [2000, 8000],
  "target_range_khz": [2.0, 8.0],
  "target_range_pass": true,
  "solver_backend": "arpack",
  "output_dir": "/tmp/jax_modal_results/v1_cricket_fine_...",
  "summary_png": "/tmp/.../summary_figures/modal_run_summary.png",
  "csv_path": "/tmp/.../modal_comprehensive_report.csv",
  "mesh_vtu": "/tmp/.../mesh/volume_mesh.vtu"
}

© lamm-mit, Apache-2.0. 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 2 other files (scripts) in skills/jax-modal-analysis of lamm-mit/scienceclaw.

• SKILL.md
• scripts/__pycache__/jax_modal_analysis.cpython-313.pyc
• scripts/jax_modal_analysis.py

Open the folder on GitHubat commit ab9aba1