Create Publication-Ready Matplotlib Charts
Plotting with Matplotlib can be hard to structure, style, and export consistently. This skill guides chart design, figure layout, styling, troubleshooting, and export choices.
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Review the Skillstore skill "matplotlib" from https://skillstore.io/skills/davila7-matplotlib.md and its manifest at https://skillstore.io/api/skills/davila7-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.
Use these links when an AI agent, crawler, or script needs clean context instead of reading the full page.
Using "matplotlib". Create a monthly revenue trend chart for a report.
Expected outcome:
A line chart plan with labeled axes, a clear title, readable ticks, a legend, and high-resolution PNG export guidance.
Using "matplotlib". Compare three distributions for a research figure.
Expected outcome:
A recommended box or violin plot layout with consistent styling, accessible colors, annotations, and vector export guidance.
Using "matplotlib". Fix a crowded figure with overlapping labels.
Expected outcome:
A troubleshooting checklist covering figure size, constrained layout, tick rotation, legend placement, and bounding-box export settings.
Most static findings are false positives caused by markdown code fences, plotting terminology, and documentation links. One medium filesystem risk is confirmed because style_configurator.py writes to a user-supplied output path. No evidence of prompt injection, data exfiltration, or hidden command execution was found.
These are real local capabilities that may be expected for this skill, so they require review but are not counted as confirmed malicious behavior.
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https://skillstore.io/skills/davila7-matplotlib/audits/15?utm_source=security_passport&utm_medium=share&utm_campaign=versioned_report[](https://skillstore.io/skills/davila7-matplotlib?utm_source=security_passport_badge)<a href="https://skillstore.io/skills/davila7-matplotlib?utm_source=security_passport_badge"><img src="https://skillstore.io/badges/skills/davila7-matplotlib/security.svg" alt="Skillstore security assessment" loading="lazy"></a><iframe src="https://skillstore.io/embed/skills/davila7-matplotlib.html" title="Skillstore Security Assessment" sandbox="allow-popups allow-popups-to-escape-sandbox" loading="lazy" referrerpolicy="no-referrer" width="420" height="180"></iframe>davila7. (2026). matplotlib security audit report (audit version 15) [Author version unspecified]. Skillstore. https://skillstore.io/skills/davila7-matplotlib/audits/15@techreport{davila7-davila7-matplotlib-2026,
author = {davila7},
title = {matplotlib security audit report (audit version 15)},
institution = {Skillstore},
year = {2026},
number = {15},
url = {https://skillstore.io/skills/davila7-matplotlib/audits/15},
note = {Author version unspecified}
}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 15)"
version: "unspecified"
type: report
authors:
- name: "davila7"
date-released: "2026-07-09"
url: "https://skillstore.io/skills/davila7-matplotlib/audits/15"
identifiers:
- type: other
value: "skillstore:davila7-matplotlib:audit:15"
description: "Skillstore immutable audit report identifier"
Each 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
Create readable plots for exploratory analysis, model diagnostics, and recurring reports.
Design multi-panel figures with controlled layout, color, labels, and export resolution.
Add consistent Matplotlib figures to notebooks, scripts, dashboards, or GUI applications.
Use the Matplotlib skill to create a clear line plot from my x and y data. Include labels, title, legend, and save settings.
Review my Matplotlib figure goal and suggest styling choices for colors, fonts, grid lines, legend placement, and accessible contrast.
Design a Matplotlib layout for four related plots. Recommend subplot structure, shared axes, annotations, spacing, and export settings.
Plan a publication-quality Matplotlib workflow for my research figure. Include layout strategy, colormap selection, typography, file formats, and troubleshooting checks.
Author
davila7License
MIT
Skillstore revision
r1
Version notice
The author did not declare a version.
Ref
b959ebfd1043a07c0c4378ab94ca4342cb0259f5
Maintenance freshness
7/20/2026
Usage
17 downloads · 232 views
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