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>- 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 | $0.00018 | $0.05456 |
| Opus 5 | $0.00009 | $0.02728 |
| Sonnet 5 | $0.00004 | $0.01091 |
| Haiku 4.5 | $0.00002 | $0.00546 |
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 10d 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.
How it starts
The opening of the file, as written. The whole thing — 527 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.
- 10d ago First seen · 527 lines · 18 tokens per session scan A c9f52cdd2d0d
generate_publication_figures is a skill published in the GitHub repository equinor/neqsim (151 stars, last pushed today), licensed Apache-2.0. It adds 18 tokens to every session and 5,456 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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