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/create-hydraulic-modelWrote 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/create-hydraulic-model)<a href="https://agentmods.dev/skills/wolframresearch/system-modeler-ai-toolkit/create-hydraulic-model"><img src="https://agentmods.dev/badge/skills/wolframresearch/system-modeler-ai-toolkit/create-hydraulic-model/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/create-hydraulic-model"><img src="https://agentmods.dev/badge/skills/wolframresearch/system-modeler-ai-toolkit/create-hydraulic-model.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 | $0.00128 | $0.07906 |
| Opus 5.5 | $0.00051 | $0.03162 |
| Sonnet 5.5 | $0.00026 | $0.01581 |
| Haiku 4.5 | $0.00013 | $0.00791 |
Grade C, and why
create-hydraulic-model 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 — 664 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Create Hydraulic Model (Graph RAG Guided)
This skill uses a knowledge graph of the Hydraulic Modelica library to guide the user through creating valid hydraulic circuit models. The graph (built from Hydraulic 2.1) contains 168 parsed components with their ports, parameters, inheritance, and 60 validated connection patterns extracted from the library's composite models and 18 example circuits.
Before you run anything
The query commands below run python -m Hydraulic.main …; the optional validation step
(Step 7) additionally drives the shared launcher. For the Windows-vs-Unix shell/Python
rules (PowerShell on Windows, python vs python3) and launcher conventions, see
the shared-conventions appendix at the end of this file — the launcher-specific parts (temp dirs,
JSON output, MSL, --load-library) only matter once you validate.
Knowledge Graph (bundled)
The Graph RAG dataset and query module ship inside this skill as the
Hydraulic/ Python package — there is nothing external to locate. The query
path reads the prebuilt graph in Hydraulic/data/graph.json; it does not
need the Modelica library and does not re-parse anything, so it works wherever
the skill is installed.
- Requirement:
networkx— but you don't install it by hand.Hydraulic.mainself-provisions it into a managed venv on first run (it never touches system Python). To pre-warm:python3 "<scripts-dir>/bootstrap_env.py" networkx. - Run the query module with this skill's own directory (the folder
containing this
SKILL.md) as the working directory, so the package resolves asHydraulic.
Query Commands
Run from this skill's directory (<skill-dir> below — the folder that contains
this SKILL.md) so the Hydraulic package is importable. Use python instead
of python3 on Windows if that's what's on PATH.
cd "<skill-dir>"
# Search for components by keyword
python3 -m Hydraulic.main --query "pump"
# Get the full effective interface of a component (ports + parameters, incl. inherited)
python3 -m Hydraulic.main --details "CylinderDouble"
# Find all components that extend an interface
python3 -m Hydraulic.main --interface "FourPort"
# List all example circuits
python3 -m Hydraulic.main --examples
# Get RAG context for a natural language query
python3 -m Hydraulic.main --rag "pressure control circuit"
What ships with it
4 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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 74ed07611656
- 23d ago Changed · +104 lines ff8cb8b53889
- 1mo ago First seen · 556 lines · 128 tokens per session scan C ebcf85c307ea
create-hydraulic-model is a skill published in the GitHub repository WolframResearch/system-modeler-ai-toolkit (17 stars, last pushed 9d ago), licensed MIT. It adds 128 tokens to every session and 7,906 once invoked, about $0.0005 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.
Other skills, from other repositories
instrument-data-to-allotrope
Convert laboratory instrument output files (PDF, CSV, Excel, TXT) to Allotrope Simple Model (ASM) JSON format or flattened 2D CSV. Use this skill when scientists need to standardize instrument data for LIMS systems, data lakes, or downstream analysis. Supports auto-detection of instrument types. Outputs include full…
matlab
Builds, reviews, migrates, and plans MATLAB or GNU Octave numerical workflows. Use for arrays, tabular/time data, tests, projects, graphics, MAT files, and explicit Python interoperability.
exploratory-data-analysis
Performs bounded, local exploratory analysis of explicitly supported scientific files. Supports redacted CSV/TSV/JSON profiles; optional NumPy, HDF5, FASTA/FASTQ, and basic image metadata inspection; missingness/leakage audits; outlier and transformation sensitivity; and rigorous EDA report scaffolds. Other domain…
phylogenetics
Builds and analyzes phylogenetic trees using MAFFT multiple sequence alignment, IQ-TREE maximum likelihood with ModelFinder and branch support, and FastTree approximate inference. Uses ETE3 for tree summaries and visualization. Applies to homologous nucleotide or protein sequences, microbial gene trees, protein…
research-engineer
An uncompromising Academic Research Engineer. Operates with absolute scientific rigor, objective criticism, and zero flair. Focuses on theoretical correctness, formal verification, and optimal implementation across any required technology.
mapping-to-snomed
Maps clinical concept spans extracted by OpenMed to SNOMED CT concepts through a USER-SUPPLIED terminology server (the user's own Ontoserver, Snowstorm, or UMLS/UTS), never a bundled vocabulary. Use when the user wants to code findings, disorders, procedures, body structures, or substances to SNOMED CT, run an ECL…