Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/WolframResearch/system-modeler-ai-toolkitnpx agentmods add skills/wolframresearch/system-modeler-ai-toolkit/simulate-modelicaWrote 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/wolframresearch/system-modeler-ai-toolkit/simulate-modelica)<a href="https://agentmods.dev/skills/wolframresearch/system-modeler-ai-toolkit/simulate-modelica"><img src="https://agentmods.dev/badge/skills/wolframresearch/system-modeler-ai-toolkit/simulate-modelica/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/wolframresearch/system-modeler-ai-toolkit/simulate-modelica"><img src="https://agentmods.dev/badge/skills/wolframresearch/system-modeler-ai-toolkit/simulate-modelica.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 | $0.00179 | $0.06111 |
| Opus 5.5 | $0.00072 | $0.02444 |
| Sonnet 5.5 | $0.00036 | $0.01222 |
| Haiku 4.5 | $0.00018 | $0.00611 |
Grade C, and why
simulate-modelica scanned grade C with 1 finding 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 9d 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.
Recursive force deletehighDestructive command
rm -rf with a variable or a broad path is one typo away from removing the wrong tree.
shell-agnostic. For cleanup use `Remove-Item -Recurse -Force`, not `rm -rf`. How it starts
The opening of the file, as written. The whole thing — 425 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Simulate Modelica Model
This skill simulates Modelica models (.mo files) with WSMKernelX: it flattens the model, generates C++ code, compiles it, and runs the simulation. It produces a .mat results file.
Before you run anything
This skill drives WSMKernelX through the shared launcher
../scripts/wsm_run.py. Read the shared-conventions appendix at the end of this file
first — launcher resolution, the Windows-vs-Unix shell/Python rules, the
temp-dir and cleanup conventions, the JSON-array output gotcha, and the MSL 4.x
dialect notes that every step below assumes.
The launcher works in _wsm_simulate_temp/ next to the .mo file and leaves
simulate.out.json and the .mat there. Tell the user: "Working in temporary
directory _wsm_simulate_temp/. This will be deleted after simulation."
Workflow
1. Identify the model file and name
Identify the .mo file and extract the model name — see Appendix → Picking the model name. For a directory-form (multi-file) library, point --model at the library folder (not one class file) and pass the full dotted --name — see Appendix → Directory-form (multi-file) libraries.
2. Run the simulation
python3 "<scripts-dir>/wsm_run.py" --mode simulate \
--model "<path-to-ModelFile.mo>" --name ModelName --timeout 180
Terser loop: add --quiet to print only a one-line outcome (status + integration
time + result file) instead of the full kernel log, and --report "Vout,x.T" to print a
compact min/max/mean/pp/final table of those variables straight from the result .mat —
so the common "simulate then inspect a few values" step is a single call. (--report
runs mat_summary.py, which you can also call standalone on any .mat.)
The launcher auto-detects MSL usage and loads the right version; force it with
--msl yes|no or --msl-version 4.1.0. If the model uses an installed non-MSL
library (e.g. Hydraulic), add --load-library <Name> — see
Appendix → Using non-MSL libraries.
Timeout: allow up to 180 seconds — compilation and simulation of complex models can take time.
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.
- 9d ago Changed · +4 lines cd31ab4c9f6f
- 23d ago Changed · +108 lines · +8 tokens per session a10aaa8d184a
- 1mo ago First seen · 313 lines · 171 tokens per session scan C c22b25c06db3
simulate-modelica is a skill published in the GitHub repository WolframResearch/system-modeler-ai-toolkit (17 stars, last pushed 9d ago), licensed MIT. It adds 179 tokens to every session and 6,111 once invoked, about $0.0007 per session on Opus 5.5. A static security scan graded it C with 1 finding (recursive force delete). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.
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