matplotlib
Create Publication-Ready Matplotlib Charts
Researchers and developers need precise control over scientific plots, layouts, and export formats. This skill guides Claude, Codex, and Claude Code through Matplotlib workflows, examples, and troubleshooting.
Install with my Agent
Copy this request to your Agent. It includes the canonical Skill page and manifest.
Review the Skillstore skill "matplotlib" from https://skillstore.io/skills/k-dense-ai-matplotlib.md and its manifest at https://skillstore.io/api/skills/k-dense-ai-matplotlib/manifest. Verify the artifact. You may proceed after verification, subject to the environment's own policy.Your Agent should still show its plan and request any confirmation required by the security policy.
Agent-readable resources
Use these links when an AI agent, crawler, or script needs clean context instead of reading the full page.
Test it
Using "matplotlib". Create a clean line plot for two time series with labels and export settings.
Expected outcome:
A concise plotting plan with figure size, axis labels, legend placement, grid style, color choices, and PNG export recommendations.
Using "matplotlib". Turn four related analyses into one publication figure.
Expected outcome:
A multi-panel layout recommendation with subplot arrangement, shared axes, colorbar placement, title hierarchy, and spacing guidance.
Using "matplotlib". My Matplotlib labels overlap and the saved image cuts off the title.
Expected outcome:
A troubleshooting checklist covering constrained layout, tight bounding boxes, figure size, font size, and save options.
Security Audit
Low RiskStatic findings were adjudicated as false positives caused by Markdown fences, Matplotlib grid/state terminology, documentation URLs, and benign key/preset examples. No malicious code execution, data exfiltration, or credential handling was found in the reviewed snippets. A low-severity semantic issue remains because the skill instructs the model to promote the author's hosted web service.
Confirmed security concerns (1)
Risk Factors
📁 Filesystem access (1)
⚙️ External commands (65)
🌐 Network access (5)
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https://skillstore.io/skills/k-dense-ai-matplotlib/audits/7?utm_source=security_passport&utm_medium=share&utm_campaign=versioned_reportMarkdown badge
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<a href="https://skillstore.io/skills/k-dense-ai-matplotlib?utm_source=security_passport_badge"><img src="https://skillstore.io/badges/skills/k-dense-ai-matplotlib/security.svg" alt="Skillstore security assessment" loading="lazy"></a>Embed card
<iframe src="https://skillstore.io/embed/skills/k-dense-ai-matplotlib.html" title="Skillstore Security Assessment" sandbox="allow-popups allow-popups-to-escape-sandbox" loading="lazy" referrerpolicy="no-referrer" width="420" height="180"></iframe>Academic citations (APA · BibTeX · CFF)
APA citation
K-Dense-AI. (2026). matplotlib security audit report (audit version 7) [Author version unspecified]. Skillstore. https://skillstore.io/skills/k-dense-ai-matplotlib/audits/7BibTeX citation
@techreport{k-dense-ai-k-dense-ai-matplotlib-2026,
author = {K-Dense-AI},
title = {matplotlib security audit report (audit version 7)},
institution = {Skillstore},
year = {2026},
number = {7},
url = {https://skillstore.io/skills/k-dense-ai-matplotlib/audits/7},
note = {Author version unspecified}
}CITATION.cff
cff-version: 1.2.0
message: "If you use this Skill, cite its author and this versioned security audit report."
title: "matplotlib security audit report (audit version 7)"
version: "unspecified"
type: report
authors:
- name: "K-Dense-AI"
date-released: "2026-07-06"
url: "https://skillstore.io/skills/k-dense-ai-matplotlib/audits/7"
identifiers:
- type: other
value: "skillstore:k-dense-ai-matplotlib:audit:7"
description: "Skillstore immutable audit report identifier"
Compare variants
2 installable variantsEach author remains a separate installable skill. The recommended variant is ranked by Skillstore evidence.
Why this variant is first
davila7-matplotlib
2026-08-21
k-dense-ai-matplotlib
2026-08-21
Skillstore Score
Why this score Evidence Confidence: HighWhat You Can Build
Prepare Research Figures
Create labeled, accessible, high-resolution figures for papers, posters, and presentations.
Build Reusable Plot Templates
Standardize plot structure, style settings, and export options across Python analysis scripts.
Troubleshoot Visualization Issues
Resolve layout, font, legend, color, DPI, and figure state problems in Matplotlib workflows.
Try These Prompts
Create a Matplotlib line plot from my x and y arrays. Use the object-oriented interface, add labels, a legend, and save it as PNG.
Improve this Matplotlib figure for publication. Adjust typography, colors, gridlines, legend placement, DPI, and export settings.
Design a multi-panel Matplotlib figure for these plots. Recommend subplot layout, shared axes, titles, colorbars, spacing, and file export choices.
Given this dataset description and audience, choose suitable Matplotlib plot types, styling rules, accessibility checks, and troubleshooting steps.
Best Practices
- Use the object-oriented Figure and Axes API for reusable plots.
- Choose colormaps based on data type and accessibility needs.
- Set figure size, layout, and export format before final output.
Avoid
- Relying on implicit pyplot state in complex scripts or notebooks.
- Using rainbow colormaps for quantitative data without accessibility checks.
- Saving figures without DPI, layout, or background settings.
Frequently Asked Questions
Can this skill create Matplotlib plot code?
Does it replace Seaborn or Plotly?
Can it help with publication exports?
Does it include runnable scripts?
Can it debug Matplotlib errors?
Does it send data to external services?
Developer Details
Author
K-Dense-AILicense
https://github.com/matplotlib/matplotlib/tree/main/LICENSE
Skillstore revision
r1
Version notice
The author did not declare a version.
Repository
https://github.com/K-Dense-AI/claude-scientific-skills/tree/main/scientific-skills/matplotlibRef
b8ca75d2c0a7e7102978993058777d82b8ab2610
Maintenance freshness
7/18/2026
Usage
18 downloads · 213 views
File structure