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.
npx skills add SFETNI/Deep-Matter-Chem-Skills --skill fem-multiphysicsgit clone --depth 1 https://github.com/SFETNI/Deep-Matter-Chem-SkillsWrote 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.
[](https://agentmods.dev/skills/sfetni/deep-matter-chem-skills/fem-multiphysics)<a href="https://agentmods.dev/skills/sfetni/deep-matter-chem-skills/fem-multiphysics"><img src="https://agentmods.dev/badge/skills/sfetni/deep-matter-chem-skills/fem-multiphysics/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/sfetni/deep-matter-chem-skills/fem-multiphysics"><img src="https://agentmods.dev/badge/skills/sfetni/deep-matter-chem-skills/fem-multiphysics.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00006 | $0.03868 |
| Opus 5 | $0.00003 | $0.01934 |
| Sonnet 5 | $0.00001 | $0.00774 |
| Haiku 4.5 | $0.00001 | $0.00387 |
Grade A, and why
fem-multiphysics 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 11d 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.
How it starts
The opening of the file, as written. The whole thing — 283 lines — stays where its author put it; the contents beside it link to each section on GitHub.
FEM Multiphysics
Description
This skill covers finite element modeling for materials, chemistry, mechanics, transport, and coupled multiphysics problems: weak-form construction, boundary and initial conditions, mesh generation, element choice, solver selection, parameter calibration, convergence studies, validation, uncertainty analysis, and reproducible implementation in FEniCS/FEniCSx, MOOSE, deal.II, COMSOL-style workflows, or similar tools. Invoke this skill when a continuum model requires spatially resolved fields in complex geometries or coupled PDEs that cannot be handled reliably by simple lumped models or closed-form approximations.
Domain Context
Finite element modeling approximates continuum field equations by converting strong-form PDEs into weak or variational forms on a mesh. Unknown fields such as displacement, concentration, temperature, electric potential, phase fraction, or pressure are represented by basis functions over elements. Boundary conditions, source terms, material laws, and coupling terms determine whether the simulation represents the physical problem or only a numerically polished artifact.
FEM is most powerful when geometry, heterogeneous materials, boundary conditions, or coupled physics matter. It is not automatically predictive: the constitutive model, parameters, mesh, time integration, nonlinear solver tolerances, and validation data define the credibility of the result. Visually smooth stress, temperature, or concentration fields can be wrong if the boundary conditions, units, material model, or mesh convergence are wrong.
For materials and chemistry, FEM often connects thermodynamics, kinetics, mechanics, and transport: diffusion with stress coupling, heat transfer during processing, electrochemical transport in porous electrodes, fracture and plasticity, elastic coherency around precipitates, and multiphysics phase-field models. Coupling can be monolithic, with all fields solved in one nonlinear system, or staggered, with physics blocks solved sequentially. The right choice depends on stiffness, coupling strength, stability, implementation complexity, and available solvers. [EXPERT REVIEW NEEDED]
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.
- 11d ago First seen · 283 lines · 6 tokens per session scan A a0b6718a78bb
fem-multiphysics is a skill published in the GitHub repository SFETNI/Deep-Matter-Chem-Skills (6 stars, last pushed 1mo ago), licensed MIT. It adds 6 tokens to every session and 3,868 once invoked, about $0.0000 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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