Scientific Agent Skills is a collection of reusable procedures that give AI agents capabilities for scientific research across areas such as biology, chemistry, medicine, and drug discovery. It is used by researchers and by people building AI scientist workflows with compatible coding agents. The catalogue contains many of the project's skills and supporting instructions.
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 K-Dense-AI/scientific-agent-skills --skill matplotlibgit clone --depth 1 https://github.com/K-Dense-AI/scientific-agent-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/k-dense-ai/scientific-agent-skills/matplotlib)<a href="https://agentmods.dev/skills/k-dense-ai/scientific-agent-skills/matplotlib"><img src="https://agentmods.dev/badge/skills/k-dense-ai/scientific-agent-skills/matplotlib/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/k-dense-ai/scientific-agent-skills/matplotlib"><img src="https://agentmods.dev/badge/skills/k-dense-ai/scientific-agent-skills/matplotlib.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- 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 | $0.00072 | $0.04189 |
| Opus 5.5 | $0.00029 | $0.01676 |
| Sonnet 5.5 | $0.00014 | $0.00838 |
| Haiku 4.5 | $0.00007 | $0.00419 |
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 23d 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.
Copies of this mod
8 near-identical copies found in the catalogue:
- matplotlib — 88% identical, 134 lines differ
- matplotlib — 86% identical, 134 lines differ
- matplotlib — 84% identical, 133 lines differ
- matplotlib — 83% identical, 134 lines differ
- matplotlib — 83% identical, 134 lines differ
- matplotlib — 83% identical, 134 lines differ
- matplotlib — 83% identical, 134 lines differ
- matplotlib — 81% identical, 137 lines differ
How it starts
The opening of the file, as written. The whole thing — 436 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==3.11.2" numpy scipy
For notebook interactivity:
uv add "matplotlib==3.11.2" ipympl
Then enable the widget backend in Jupyter with %matplotlib widget or %matplotlib ipympl.
Targets Matplotlib 3.11.2 (Python 3.11+), reviewed 2026-10-01. The bundled
scripts and representative examples were executed using Agg and PNG/PDF/SVG output.
GUI windows, Jupyter widgets, and external LaTeX are environment-dependent and were
not exercised. Fragment examples assume imports and named data; adapt and validate
them before use. Check the 3.11 API changes
when migrating older code: use tick_labels and orientation for box plots,
mpl.colormaps[name] for colormaps, and label contour lines rather than contourf.
File output needs no GUI. Use MPLBACKEND=Agg for batch scripts, or select Agg before
importing pyplot. Interactive output requires an installed GUI toolkit such as
PySide6 (QtAgg) or working Tk (TkAgg); plt.ioff() does not remove GUI thread
requirements. See backends.
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.
- 23d ago Changed · +35 lines · -5 tokens per session 60b80aaa802e
- 24d ago Changed · +6 lines d3944b415a53
- 1mo ago First seen · 395 lines · 77 tokens per session scan A 57c8fb3c504a
matplotlib is a skill published in the GitHub repository K-Dense-AI/scientific-agent-skills (54,470 stars, last pushed 6d ago), licensed MIT. It adds 72 tokens to every session and 4,189 once invoked, about $0.0003 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 2026-09-03.
Other skills, from other repositories
discovery-toolbox
A routed repertoire of 90 scientific thinking operators for biological research agents - visual reasoning, detectability and information budgets, search reframing, causal identification, competing explanations, observation and selection processes, pipeline artifact diagnosis, effort allocation, and confirmation…
discovery-director
Operate as a research director making original discoveries from a given biological question and dataset. Use when the task is open-ended scientific research, exploring omics or experimental data for findings, hypothesis generation and testing, screening a large candidate space of genes, variants, features or…
demo-builder
Builds personalized demo assets for top prospects using the founder's product API/MCP/SDK. Researches prospect, proposes demo concepts, builds working prototype, tests it, and generates comparison report with live demo link.
meta-ad-manager
Front door and loop owner of a Meta (Facebook/Instagram) ad harness. Reads the brand's ads/ docs, works out which campaign the user means and which stage it is at, hands off to the stage skill that runs it (intake, strategy, creative, launch, checks, fixes, answers), and writes every stage change back to the docs. Use…
industry-scanner
Daily industry intelligence scanner. Scans web, social media, news, blogs, and communities for industry-relevant events, trends, and signals. Produces a comprehensive intelligence briefing plus strategic GTM opportunity ideas. Orchestrates existing scraping skills — does not reimplement data collection.
inbound-lead-enrichment
Fills in missing data for inbound leads — researches the company, identifies the person's role and seniority, finds other stakeholders at the company, checks for existing CRM relationships, and updates the lead record. Produces enriched lead data ready for qualification or outreach. Tool-agnostic.