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 agentmods add skills/lzy599775/agent-auto-sci-skills/matplotlibnpx skills add Lzy599775/agent-auto-sci-skills --skill matplotlibgit clone --depth 1 https://github.com/Lzy599775/agent-auto-sci-skillsWrote 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/lzy599775/agent-auto-sci-skills/matplotlib)<a href="https://agentmods.dev/skills/lzy599775/agent-auto-sci-skills/matplotlib"><img src="https://agentmods.dev/badge/skills/lzy599775/agent-auto-sci-skills/matplotlib.svg" alt="Measured on agentmods" height="20"></a>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 | $0.00077 | $0.03155 |
| Opus 5 | $0.00039 | $0.01577 |
| Sonnet 5 | $0.00015 | $0.00631 |
| Haiku 4.5 | $0.00008 | $0.00315 |
Grade A, and why
matplotlib 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 3d 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 — 379 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Matplotlib
Overview
Matplotlib is Python's foundational visualization library for creating static, animated, and interactive plots. This skill provides guidance on using matplotlib effectively, covering both the pyplot interface (MATLAB-style) and the object-oriented API (Figure/Axes), along with best practices for creating publication-quality visualizations.
When to Use This Skill
This skill should be used when:
- Creating any type of plot or chart (line, scatter, bar, histogram, heatmap, contour, etc.)
- Generating scientific or statistical visualizations
- Customizing plot appearance (colors, styles, labels, legends)
- Creating multi-panel figures with subplots
- Exporting visualizations to various formats (PNG, PDF, SVG, etc.)
- Building interactive plots or animations
- Working with 3D visualizations
- Integrating plots into Jupyter notebooks or GUI applications
Setup
For project work, install Matplotlib with uv:
uv add matplotlib
For notebook interactivity:
uv add matplotlib ipympl
Then enable the widget backend in Jupyter with %matplotlib widget or %matplotlib ipympl.
Matplotlib 3.10 requires Python 3.10+ and NumPy 1.23+. Non-interactive file output works through backends such as Agg, PDF, and SVG. For GUI windows, Matplotlib auto-selects an available backend; if TkAgg fails in a uv-managed Python, update uv and Python builds with uv self update and uv python upgrade --reinstall, or install a Qt backend with uv add pyside6.
Core Concepts
The Matplotlib Hierarchy
Matplotlib uses a hierarchical structure of objects:
- Figure - The top-level container for all plot elements
- Axes - The actual plotting area where data is displayed (one Figure can contain multiple Axes)
- Artist - Everything visible on the figure (lines, text, ticks, etc.)
- Axis - The number line objects (x-axis, y-axis) that handle ticks and labels
Two Interfaces
1. pyplot Interface (Implicit, MATLAB-style)
import matplotlib.pyplot as plt
plt.plot([1, 2, 3, 4])
plt.ylabel('some numbers')
plt.show()
- Convenient for quick, simple plots
- Maintains state automatically
- Good for interactive work and simple scripts
What ships with it
6 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 3d ago First seen · 379 lines · 77 tokens per session scan A 3558028333b2
matplotlib is a skill published in the GitHub repository Lzy599775/agent-auto-sci-skills (2 stars, last pushed 9d ago), licensed MIT. It adds 77 tokens to every session and 3,155 once invoked, about $0.0004 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 2026-08-31.
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