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matplotlib-charts

Generate standardized PNG charts with matplotlib for headless workflows.

94|7|Updated Feb 10, 2026
Search Tags:#png#data visualization#reporting#plotting#matplotlib#chart
One-click install
npx skills add https://github.com/jin-bo/agentao --skill matplotlib-charts
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: matplotlib-charts
Source: https://github.com/jin-bo/agentao/tree/main/examples/data-workbench/.agentao/skills/matplotlib-charts
Command: npx skills add https://github.com/jin-bo/agentao --skill matplotlib-charts

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill eliminates the hassle of manually configuring chart settings and troubleshooting headless environment errors when creating data visualizations for reports and presentations.

Core Features & Use Cases

  • Consistent chart formatting: Enforces standard figsize, DPI, and readable labels for all outputs.
  • Headless runtime support: Works seamlessly in non-interactive agent environments without display servers.
  • Use case: Convert sales data, user metrics, or research results into clear bar, line, or scatter charts for stakeholder reports and dashboards.

Quick Start

Ask the agent to generate a bar chart of your monthly revenue data and save it as a PNG file in your working directory.

Frequently Asked Questions about matplotlib-charts

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I generate matplotlib PNG charts in a headless agent environment?▼

To generate matplotlib PNG charts in a headless environment, this Skill applies standardized formatting and fixed naming conventions to produce predictable, high-resolution plot files without requiring a display server.

Why do my matplotlib plots fail to render in automated reporting workflows?▼

Matplotlib plots often fail in automated reporting workflows due to missing display servers. This Skill resolves headless runtime errors by applying a standardized, agent-driven configuration to output PNG files directly.

What is the best way to ensure consistent formatting across multiple data visualization PNG outputs?▼

Consistent formatting for data visualization PNG outputs is achieved by enforcing standard figsize, DPI settings, readable axis labels, and tight bounding boxes across all generated charts.

Can I use this matplotlib plotting Skill for business reporting and dashboard creation?▼

Yes, you can use this matplotlib plotting Skill for business reporting and dashboard creation. It converts sales data, user metrics, and research results into clear bar, line, or scatter charts for stakeholders.

Does this data visualization Skill require manual configuration for high-resolution plots?▼

No manual configuration is required for high-resolution plots. The Skill eliminates manual chart setup by automatically applying proper axis labels, tight bounding boxes, and standard DPI for host UI rendering.

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