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 wentorai/research-plugins --skill chart-image-generatorgit clone --depth 1 https://github.com/wentorai/research-pluginsWrote 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/wentorai/research-plugins/chart-image-generator)<a href="https://agentmods.dev/skills/wentorai/research-plugins/chart-image-generator"><img src="https://agentmods.dev/badge/skills/wentorai/research-plugins/chart-image-generator/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/wentorai/research-plugins/chart-image-generator"><img src="https://agentmods.dev/badge/skills/wentorai/research-plugins/chart-image-generator.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 | $0.00012 | $0.02136 |
| Opus 5.5 | $0.00005 | $0.00854 |
| Sonnet 5.5 | $0.00002 | $0.00427 |
| Haiku 4.5 | $0.00001 | $0.00214 |
Grade A, and why
chart-image-generator 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 1mo 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 — 230 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Chart Image Generator
A skill for generating publication-quality chart images from research data using Python visualization libraries. Covers chart type selection, styling for academic journals, multi-panel layouts, color accessibility, and export at the correct resolution and format for submission.
Overview
Creating figures for academic publications requires more than just plotting data. Journals have specific requirements for resolution (typically 300-600 DPI), file format (TIFF, EPS, PDF, or high-resolution PNG), font sizes (often 8-12pt in the final printed figure), line weights, and color accessibility. This skill automates the production of figures that meet these standards, reducing the time researchers spend on manual formatting and ensuring consistency across all figures in a manuscript.
The skill supports common chart types used in academic research: scatter plots, bar charts, line plots, box plots, violin plots, heatmaps, forest plots, Kaplan-Meier curves, and multi-panel composite figures. All examples use matplotlib and seaborn with a custom academic styling configuration.
Academic Figure Styling
Journal-Ready Style Configuration
import matplotlib.pyplot as plt
import matplotlib as mpl
def set_academic_style():
"""
Configure matplotlib for publication-quality figures.
Matches common requirements for Nature, Science, PLOS, IEEE journals.
"""
plt.rcParams.update({
# Font settings
'font.family': 'sans-serif',
'font.sans-serif': ['Arial', 'Helvetica', 'DejaVu Sans'],
'font.size': 8,
'axes.titlesize': 9,
'axes.labelsize': 8,
'xtick.labelsize': 7,
'ytick.labelsize': 7,
'legend.fontsize': 7,
# Line and marker settings
'lines.linewidth': 1.0,
'lines.markersize': 4,
'axes.linewidth': 0.5,
'xtick.major.width': 0.5,
'ytick.major.width': 0.5,
# Grid and background
'axes.grid': False,
'axes.facecolor': 'white',
'figure.facecolor': 'white',
# Legend
'legend.frameon': False,
'legend.borderpad': 0.3,
# Save settings
'savefig.dpi': 300,
'savefig.bbox': 'tight',
'savefig.pad_inches': 0.05,
# Use Type 1 fonts for EPS/PDF (required by many journals)
'pdf.fonttype': 42,
'ps.fonttype': 42,
})
# Common journal figure widths (in inches):
SINGLE_COLUMN = 3.5 # ~89mm (Nature, Science, PLOS)
DOUBLE_COLUMN = 7.0 # ~178mm
ONE_AND_HALF = 5.5 # ~140mm
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.
- 1mo ago First seen · 230 lines · 12 tokens per session scan A 2ed6d26446e2
chart-image-generator is a skill published in the GitHub repository wentorai/research-plugins (302 stars, last pushed 4mo ago), licensed MIT. It adds 12 tokens to every session and 2,136 once invoked, about $0.0000 per session on Opus 5.5. 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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