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 G1Joshi/Agent-Skills --skill plotlygit clone --depth 1 https://github.com/G1Joshi/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/g1joshi/agent-skills/plotly)<a href="https://agentmods.dev/skills/g1joshi/agent-skills/plotly"><img src="https://agentmods.dev/badge/skills/g1joshi/agent-skills/plotly/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/g1joshi/agent-skills/plotly"><img src="https://agentmods.dev/badge/skills/g1joshi/agent-skills/plotly.svg" alt="Reviewed on agentmods" width="80" 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 5.1 | $0.00037 | $0.01402 |
| Opus 5.5 | $0.00015 | $0.00561 |
| Sonnet 5.5 | $0.00007 | $0.00280 |
| Haiku 4.5 | $0.00004 | $0.00140 |
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 17d 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 — 168 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Plotly
Plotly generates publication-quality interactive charts, dashboards, and analytical visualizations across Python, R, and JavaScript.
When to Use
- Interactive Web Dashboards & Visualizations: Building zoomable, pan-able, and hover-interactive charts in Python/JS.
- Financial & Candlestick Charts: Displaying high-frequency stock, crypto, and commodity data with interactive range sliders.
- 3D Surface & Geospatial Mapping: Rendering 3D point clouds, geospatial choropleth maps, and WebGL scatter plots.
- Jupyter & Streamlit Integration: Embedding interactive visualizations into Streamlit, Dash, or JupyterLab.
Quick Start
import plotly.express as px
# Create interactive scatter plot with hover tooltips and trendline
df = px.data.iris()
fig = px.scatter(
df, x="sepal_width", y="sepal_length",
color="species", size="petal_length",
hover_data=["petal_width"],
title="Iris Dataset - Interactive Feature Exploration"
)
# Open in browser or render in Jupyter
fig.show()
Core Concepts
High-Level Charting with Plotly Express
Generating rich multi-variable interactive charts in one line:
import plotly.express as px
import pandas as pd
# Load sample dataset
df = px.data.gapminder().query("year == 2007")
fig = px.scatter(
df,
x="gdpPercap",
y="lifeExp",
size="pop",
color="continent",
hover_name="country",
log_x=True,
size_max=60,
title="Global Health vs. Wealth (2007)",
labels={"gdpPercap": "GDP per Capita (USD)", "lifeExp": "Life Expectancy (Years)"},
template="plotly_white"
)
# Customize hover tooltip formatting
fig.update_traces(
hovertemplate="<b>%{hovertext}</b><br>GDP/Capita: $%{x:,.2f}<br>Life Expectancy: %{y:.1f} yrs<extra></extra>"
)
# Export interactive HTML widget
fig.write_html("interactive_scatter.html", include_plotlyjs="cdn")
Financial Candlestick Chart with Range Slider (graph_objects)
Detailed technical analysis with interactive time navigation:
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.
- 17d ago Changed · +5 lines a4bf058bd4bb
- 21d ago Changed · +119 lines · +23 tokens per session 56547886f95f
- 1mo ago First seen · 44 lines · 14 tokens per session scan A 878133e0e0ba
plotly is a skill published in the GitHub repository G1Joshi/Agent-Skills (15 stars, last pushed 18d ago), licensed MIT. It adds 37 tokens to every session and 1,402 once invoked, about $0.0001 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 2026-08-30.
Other skills, from other repositories
context-engineering
Optimizes agent context setup. Use when starting a new session, when agent output quality degrades, when switching between tasks, or when you need to configure rules files and context for a project.
doubt-driven-development
Subjects every non-trivial decision to a fresh-context adversarial review before it stands. Use when you want every assumption cross-examined before proceeding, when stress-testing a plan for hidden failure modes, when correctness matters more than speed, when working in unfamiliar code, when stakes are high…
git-workflow-and-versioning
Structures git workflow practices. Use when making any code change. Use when committing, branching, resolving conflicts, splitting uncommitted work in a messy working tree into clean atomic commits, opening or reviewing a pull request (PR), pushing to a remote, or when you need to organize work across multiple…
observability-and-instrumentation
Instruments code so production behavior is visible and diagnosable. Use when adding logging, metrics, tracing, or alerting. Use when shipping any feature that runs in production and you need evidence it works. Use when production issues are reported but you can't tell what happened from the available data.
spec-driven-development
Creates specs before coding. Use when starting a new project, feature, or significant change and no specification exists yet. Use when drafting a PRD or requirements document with objectives and scope, or when requirements are unclear, ambiguous, or only exist as a vague idea. Use when a single requirement spans…
ci-cd-and-automation
Automates CI/CD pipeline setup. Use when setting up or modifying build and deployment pipelines. Use when you need to automate quality gates, configure test runners in CI, or establish deployment strategies.