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 equinor/neqsim --skill generate-publication-figuresgit 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/skills/equinor/neqsim/generate-publication-figures)<a href="https://agentmods.dev/skills/equinor/neqsim/generate-publication-figures"><img src="https://agentmods.dev/badge/skills/equinor/neqsim/generate-publication-figures/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/generate-publication-figures"><img src="https://agentmods.dev/badge/skills/equinor/neqsim/generate-publication-figures.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 | $0.00019 | $0.05467 |
| Opus 5.5 | $0.00008 | $0.02187 |
| Sonnet 5.5 | $0.00004 | $0.01093 |
| Haiku 4.5 | $0.00002 | $0.00547 |
Grade A, and why
generate-publication-figures 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 27d 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
97% identical to generate_publication_figures — 2 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 — 528 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Skill: Generate Publication-Quality Figures
Purpose
Create matplotlib figures that meet journal submission standards: correct fonts, compact sizes, consistent styling, readable labels, and high DPI. Based on lessons learned from the CPA and TPflash papers (Fluid Phase Equilibria 2026).
SI Units (MANDATORY)
All figure axis labels MUST use SI units. See PAPER_WRITING_GUIDELINES.md "SI Units (MANDATORY)" for the full reference.
| Axis label examples (GOOD) | NEVER use |
|---|---|
Temperature (K) or $T$ (K) |
Temperature (°F) |
Pressure (kPa) or $P$ (MPa) |
Pressure (psi) or Pressure (atm) |
Density (kg/m³) or $\rho$ (kg/m$^3$) |
Density (lb/ft³) |
Viscosity (mPa·s) |
Viscosity (cP) — numerically equal but use SI name |
Flow rate (kg/s) |
Flow rate (lb/h) |
Energy (kJ/mol) |
Energy (BTU/lbmol) |
"bar" is acceptable for pressure axes in engineering contexts (1 bar = 100 kPa).
When to Use
- Creating figures for any scientific paper in the paperlab
- Regenerating figures after data or style revisions
- Setting up a new
02_generate_figures.pyfor a paper project
Core Setup (Copy-Paste Starter)
Every figure script should start with this rc configuration:
import matplotlib
matplotlib.use("Agg")
import matplotlib.pyplot as plt
import matplotlib.ticker as ticker
import numpy as np
import json
from pathlib import Path
# ── Publication-quality defaults ──────────────────────────────────
plt.rcParams.update({
"font.family": "serif",
"font.serif": ["Times New Roman", "DejaVu Serif"],
"font.size": 9,
"axes.titlesize": 10,
"axes.labelsize": 9,
"xtick.labelsize": 8,
"ytick.labelsize": 8,
"legend.fontsize": 8,
"figure.dpi": 300,
"savefig.dpi": 300,
"savefig.bbox_inches": "tight",
"axes.linewidth": 0.6,
"xtick.direction": "in",
"ytick.direction": "in",
"xtick.major.size": 3,
"ytick.major.size": 3,
"xtick.minor.size": 1.5,
"ytick.minor.size": 1.5,
"grid.linewidth": 0.3,
"grid.alpha": 0.4,
"lines.linewidth": 1.0,
"lines.markersize": 4,
})
# Consistent color palette
BLUE = "#2171b5"
ORANGE = "#e6550d"
GREEN = "#31a354"
GREY = "#636363"
PALETTE = [BLUE, ORANGE, GREEN, "#756bb1", "#e7298a", "#66a61e"]
# Output directory
FIGURES_DIR = Path(__file__).parent.parent / "figures"
FIGURES_DIR.mkdir(exist_ok=True)
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.
- 27d ago First seen · 528 lines · 19 tokens per session scan A 31432d64e7c5
generate-publication-figures is a skill published in the GitHub repository equinor/neqsim (156 stars, last pushed today), licensed Apache-2.0. It adds 19 tokens to every session and 5,467 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 97% identical to generate_publication_figures, differing in 2 lines, and is treated as a copy.
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