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/tondevrel/scientific-agent-skills/plotlynpx skills add tondevrel/scientific-agent-skills --skill plotlygit clone --depth 1 https://github.com/tondevrel/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/tondevrel/scientific-agent-skills/plotly)<a href="https://agentmods.dev/skills/tondevrel/scientific-agent-skills/plotly"><img src="https://agentmods.dev/badge/skills/tondevrel/scientific-agent-skills/plotly.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 | $0.00093 | $0.02849 |
| Opus 5 | $0.00046 | $0.01425 |
| Sonnet 5 | $0.00019 | $0.00570 |
| Haiku 4.5 | $0.00009 | $0.00285 |
Grade A, and why
plotly 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 4d 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 — 320 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Plotly - Interactive Visualization
Plotly provides a wide range of interactive charts. Its "Plotly Express" API is designed for speed and ease of use with tidy DataFrames, while "Graph Objects" offers low-level control over every trace and attribute.
When to Use
- Creating interactive charts for web applications or Jupyter notebooks
- Visualizing 3D data (surfaces, scatter, mesh)
- Geographic maps (scatter on maps, choropleths) with Mapbox integration
- Financial charts (candlestick, OHLC)
- Exploring large datasets where zooming into specific regions is required
- Creating animations (time-series sliders)
- Building production-ready dashboards (via Dash)
Reference Documentation
Official docs: https://plotly.com/python/
Plotly Express: https://plotly.com/python/plotly-express/
Search patterns: px.scatter, go.Figure, fig.update_layout, fig.write_html, px.choropleth
Core Principles
Plotly Express (px) vs. Graph Objects (go)
| Feature | Plotly Express (px) | Graph Objects (go) |
|---|---|---|
| Complexity | High-level, concise. | Low-level, verbose. |
| Data Format | Tidy (long-form) DataFrames. | Lists, Arrays, Dicts, or DataFrames. |
| Customization | Good (using update_*). | Maximum / Full control. |
| Speed of Dev | Very fast. | Slower. |
Use Plotly For
- Interactive exploration (hover, zoom)
- 3D and Geospatial visualization
- Exporting to standalone interactive HTML files
- Integration with Dash
Do NOT Use For
- Publication-quality static LaTeX plots (use Matplotlib)
- Very large static image generation (Matplotlib is faster)
- Low-memory environments (Plotly's JSON-based figures are memory-heavy)
Quick Reference
Installation
pip install plotly pandas
Standard Imports
import plotly.express as px
import plotly.graph_objects as go
import pandas as pd
import numpy as np
Basic Pattern - Plotly Express
import plotly.express as px
# Load data
df = px.data.iris()
# Create interactive scatter plot
fig = px.scatter(df, x="sepal_width", y="sepal_length",
color="species", size="petal_length",
hover_data=['petal_width'])
# Display
fig.show()
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.
- 4d ago First seen · 320 lines · 93 tokens per session scan A 1602b076d956
plotly is a skill published in the GitHub repository tondevrel/scientific-agent-skills (19 stars, last pushed 7mo ago), licensed MIT. It adds 93 tokens to every session and 2,849 once invoked, about $0.0005 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 2026-08-30.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
brainstorming
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior. Explores user intent, requirements and design before implementation.
auto-perf-optimize
Run agent-driven VS Code performance or memory investigations. Use when asked to launch Code OSS, automate a VS Code scenario, run the Chat memory smoke runner, capture renderer heap snapshots, take workflow screenshots, compare run summaries, or drive a repeatable scenario before heap-snapshot analysis.
chat-perf
Run chat perf benchmarks and memory leak checks against the local dev build or any published VS Code version. Use when investigating chat rendering regressions, validating perf-sensitive changes to chat UI, or checking for memory leaks in the chat response pipeline.
chat-pet-sprite-creation
Use when creating or changing VS Code chat pet sprite art, sprite sheets, state animations, eye treatments, Stable/Insiders variants, or pet transitions under src/vs/workbench/contrib/chat/browser/widget/media/chatPet.
cpu-profile-analysis
Analyze V8/Chrome CPU profiles (.cpuprofile) and DevTools trace files (Trace-.json). Use when: profiling performance, investigating slow functions, comparing code paths, finding bottlenecks, analyzing timeToRequest, understanding call trees from sampling profiler data, analyzing layout/paint/rendering, investigating…