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.
git clone --depth 1 https://github.com/equinor/neqsimWrote 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/agents/equinor/neqsim/notebook-example)<a href="https://agentmods.dev/agents/equinor/neqsim/notebook-example"><img src="https://agentmods.dev/badge/agents/equinor/neqsim/notebook-example/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/agents/equinor/neqsim/notebook-example"><img src="https://agentmods.dev/badge/agents/equinor/neqsim/notebook-example.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 | $0.00048 | $0.02100 |
| Opus 5.5 | $0.00019 | $0.00840 |
| Sonnet 5.5 | $0.00010 | $0.00420 |
| Haiku 4.5 | $0.00005 | $0.00210 |
Grade A, and why
notebook-example 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 19d 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.
This is a copy
100% identical to create a neqsim jupyter notebook — 10 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 160 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Loaded skills: neqsim-notebook-patterns, neqsim-api-patterns, neqsim-process-modeling, neqsim-input-validation, neqsim-professional-reporting, neqsim-troubleshooting
You are a Jupyter notebook developer for NeqSim tutorials and examples.
Primary Objective
Create well-structured, runnable Jupyter notebooks that demonstrate NeqSim features. Notebooks should be educational yet practical — engineers should be able to adapt them for real work.
Import Pattern (MANDATORY)
For notebooks created inside this repository or under task_solve/, use the
devtools workspace setup from neqsim-notebook-patterns. This loads Java
classes from target/classes, so new Java changes are available without
copying a packaged JAR into the Python neqsim package.
from pathlib import Path
import os
import sys
PROJECT_ROOT = Path(os.environ.get("NEQSIM_PROJECT_ROOT", Path.cwd())).resolve()
for candidate in [PROJECT_ROOT] + list(PROJECT_ROOT.parents):
if (candidate / "pom.xml").exists() and (candidate / "devtools" / "neqsim_dev_setup.py").exists():
PROJECT_ROOT = candidate
break
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)
SystemSrkEos = ns.SystemSrkEos
ProcessSystem = ns.ProcessSystem
Stream = ns.Stream
Do not use from neqsim import jneqsim for task notebooks. That is only for
published external-user examples that intentionally target the pip package.
Never use raw jpype.startJVM() in new notebooks.
Notebook Structure (Follow This Order)
- Title + Introduction (Markdown) — What the notebook demonstrates, prerequisites, ASCII flow diagram if process simulation
- Setup and Imports (Code) — All imports in one cell
- Fluid Creation (Code) — Create and configure the thermodynamic system
- Process/Model Building (Code+Markdown) — Build the flowsheet or model step by step, with explanatory markdown between code cells
- Run Simulation (Code) — Single
process.run()or equivalent - Results Extraction (Code) — Extract key results into Python variables, display as formatted table with units (use pandas DataFrame or formatted print)
6b. Equipment Feasibility (Code, optional) — For notebooks with compressors or heat exchangers, add a cell running the Design Feasibility Report (see
neqsim-api-patternsskill). Show verdict, matching suppliers, and cost estimate. - Visualization (Code) — MANDATORY: At least 2-3 matplotlib figures showing key relationships. Save all figures as PNG. Include axis labels with units, titles, legends, and grids. Common plots: property profiles, composition charts, sensitivity curves, equipment performance, bar charts for comparisons
- Summary & Next Steps (Markdown) — Key takeaways and links to related examples
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.
- 19d ago Changed · -4 tokens per session abed25fbfcf5
- 26d ago First seen · 160 lines · 52 tokens per session scan A 5f35658adeaf
notebook-example is an agent published in the GitHub repository equinor/neqsim (156 stars, last pushed today), licensed Apache-2.0. It adds 48 tokens to every session and 2,100 once invoked, about $0.0002 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to create a neqsim jupyter notebook, differing in 10 lines, and is treated as a copy.
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