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/equinor/neqsimnpx agentmods add skills/equinor/neqsim/neqsim-notebook-patternsWrote 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/equinor/neqsim/neqsim-notebook-patterns)<a href="https://agentmods.dev/skills/equinor/neqsim/neqsim-notebook-patterns"><img src="https://agentmods.dev/badge/skills/equinor/neqsim/neqsim-notebook-patterns/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/equinor/neqsim/neqsim-notebook-patterns"><img src="https://agentmods.dev/badge/skills/equinor/neqsim/neqsim-notebook-patterns.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00062 | $0.05623 |
| Opus 5.5 | $0.00025 | $0.02249 |
| Sonnet 5.5 | $0.00012 | $0.01125 |
| Haiku 4.5 | $0.00006 | $0.00562 |
Grade A, and why
neqsim-notebook-patterns scanned grade A 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 today.
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.
Runs shell commandslowCapability
Expected in a hook, worth knowing in a rule or an instructions file.
subprocess.run([ How it starts
The opening of the file, as written. The whole thing — 587 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Jupyter Notebook Patterns for NeqSim
Standard patterns for creating Jupyter notebooks that use workspace NeqSim Java classes via devtools.
Devtools Setup Cell (Use in Every Task Notebook)
Task notebooks under task_solve/ MUST load NeqSim through
devtools/neqsim_dev_setup.py. This puts workspace Java classes from
target/classes on the JVM classpath, so new or modified Java classes are
available without copying a packaged JAR into the neqsim Python package.
import os
import sys
from pathlib import Path
def find_neqsim_project_root():
env_root = os.environ.get("NEQSIM_PROJECT_ROOT")
candidates = []
if env_root:
candidates.append(Path(env_root).resolve())
cwd = Path.cwd().resolve()
candidates.extend([cwd] + list(cwd.parents))
for candidate in candidates:
if (candidate / "pom.xml").exists() and (candidate / "devtools" / "neqsim_dev_setup.py").exists():
return candidate
raise RuntimeError("Could not find NeqSim project root. Set NEQSIM_PROJECT_ROOT.")
PROJECT_ROOT = find_neqsim_project_root()
sys.path.insert(0, str(PROJECT_ROOT / "devtools"))
from neqsim_dev_setup import neqsim_init, neqsim_classes
ns = neqsim_init(project_root=PROJECT_ROOT, recompile=False, verbose=True)
ns = neqsim_classes(ns)
NEQSIM_MODE = "devtools"
print("NeqSim loaded via devtools workspace classes")
Class Import Cell
# Classes are already available on ns from neqsim_classes(ns):
SystemSrkEos = ns.SystemSrkEos
ProcessSystem = ns.ProcessSystem
Stream = ns.Stream
Separator = ns.Separator
Compressor = ns.Compressor
Cooler = ns.Cooler
Heater = ns.Heater
ThrottlingValve = ns.ThrottlingValve
Mixer = ns.Mixer
Splitter = ns.Splitter
Do not use from neqsim import jneqsim in task notebooks or runner workflows.
That imports the installed Python package and can miss workspace Java changes.
Only published Colab-style examples outside task_solve/ may use jneqsim as
an external-user pattern.
Common Class Paths
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.
- today Changed f453375f64cd
- 1mo ago First seen · 587 lines · 62 tokens per session scan A d933dc6853cd
neqsim-notebook-patterns is a skill published in the GitHub repository equinor/neqsim (156 stars, last pushed today), licensed Apache-2.0. It adds 62 tokens to every session and 5,623 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 1 finding (runs shell commands). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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