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Agent skill

Plotly

by davila7 in davila7/claude-code-templates

Interactive scientific and statistical data visualization library for Python.

MITAuto-check passedData & Analytics

Install Plotly

skills CLI
$ npx skills add davila7/claude-code-templates --skill plotly -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install davila7/claude-code-templates plotly --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/davila7/claude-code-templates.git skills-src && mkdir -p .claude/skills && cp -r skills-src/cli-tool/components/skills/scientific/plotly .claude/skills/plotly && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
plotly
GitHub stars
32k
Used in
14 other repos
Token cost
~1.8k tokens
SKILL.md length
369 words
Files
6
Skills in repo
477
Repo updated
First seen
Licence
MIT

At a glance

Interactive scientific and statistical data visualization library for Python.

  • Works in 4 steps: Chart Types → Layouts and Styling → Interactivity → …
  • Creating charts
  • SKILL.md covers Quick Start, Choosing Between APIs, Core Capabilities and Common Workflows, plus 3 more sections
  • Calls uv

What it does

Plotly is an agent skill from davila7/claude-code-templates. Interactive scientific and statistical data visualization library for Python. Use when creating charts, plots, or visualizations including scatter plots, line charts, bar charts, heatmaps, 3D plots, geographic maps, statistical distributions, financial charts, and dashboards. Supports both quick visualizations (Plotly Express) and fine-grained customization (graph objects). Outputs interactive HTML or static images (PNG, PDF, SVG).

Its SKILL.md is about 1.8k tokens, which your agent loads only when the skill is triggered. The skill folder holds 6 other files (for example `reference/chart-types.md`, `reference/export-interactivity.md` and `reference/graph-objects.md`).

It sits in Data & Analytics, covering Data visualization. It works with Plotly and Python. The repository describes itself as: CLI tool for configuring and monitoring Claude Code. The licence is MIT.

When your agent uses it

  • Creating charts
  • Visualizations including scatter plots
  • Geographic maps
  • Statistical distributions

Example prompts

  • “/plotly”

Requirements

  • Python 3

Workflow steps

4 steps, taken from the step headings in SKILL.md.

  1. Chart Types
  2. Layouts and Styling
  3. Interactivity
  4. Export Options

What it can do on your machine

Read from SKILL.md and the folder at commit 4c82aba. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • uv

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • plotly.com
    • community.plotly.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Plotly loads about 1.8k tokens when it runs. Until then it costs about 111 tokens; SKILL.md has 369 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~111
When it runs · the whole SKILL.md, loaded when a task matches
~1.8k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from davila7/claude-code-templates at commit 4c82aba, republished under its MIT licence (© davila7). 369 words, ~1,834 tokens.

Download SKILL.mdSave it as .claude/skills/plotly/SKILL.md (or your agent's skills folder). This skill also uses 5 other files; get the full folder from GitHub.
name
plotly
description
Interactive scientific and statistical data visualization library for Python. Use when creating charts, plots, or visualizations including scatter plots, line charts, bar charts, heatmaps, 3D plots, geographic maps, statistical distributions, financial charts, and dashboards. Supports both quick visualizations (Plotly Express) and fine-grained customization (graph objects). Outputs interactive HTML or static images (PNG, PDF, SVG).

Plotly

Python graphing library for creating interactive, publication-quality visualizations with 40+ chart types.

Quick Start

Install Plotly:

bash
uv pip install plotly

Basic usage with Plotly Express (high-level API):

python
import plotly.express as px
import pandas as pd

df = pd.DataFrame({
    'x': [1, 2, 3, 4],
    'y': [10, 11, 12, 13]
})

fig = px.scatter(df, x='x', y='y', title='My First Plot')
fig.show()

Choosing Between APIs

Use Plotly Express (px)

For quick, standard visualizations with sensible defaults:

  • Working with pandas DataFrames
  • Creating common chart types (scatter, line, bar, histogram, etc.)
  • Need automatic color encoding and legends
  • Want minimal code (1-5 lines)

See reference/plotly-express.md for complete guide.

Use Graph Objects (go)

For fine-grained control and custom visualizations:

  • Chart types not in Plotly Express (3D mesh, isosurface, complex financial charts)
  • Building complex multi-trace figures from scratch
  • Need precise control over individual components
  • Creating specialized visualizations with custom shapes and annotations

See reference/graph-objects.md for complete guide.

Note: Plotly Express returns graph objects Figure, so you can combine approaches:

python
fig = px.scatter(df, x='x', y='y')
fig.update_layout(title='Custom Title')  # Use go methods on px figure
fig.add_hline(y=10)                     # Add shapes

Core Capabilities

1. Chart Types

Plotly supports 40+ chart types organized into categories:

Basic Charts: scatter, line, bar, pie, area, bubble

Statistical Charts: histogram, box plot, violin, distribution, error bars

Scientific Charts: heatmap, contour, ternary, image display

Financial Charts: candlestick, OHLC, waterfall, funnel, time series

Maps: scatter maps, choropleth, density maps (geographic visualization)

3D Charts: scatter3d, surface, mesh, cone, volume

Specialized: sunburst, treemap, sankey, parallel coordinates, gauge

For detailed examples and usage of all chart types, see reference/chart-types.md.

Show full SKILL.md (165 more words)Show less
2. Layouts and Styling

Subplots: Create multi-plot figures with shared axes:

python
from plotly.subplots import make_subplots
import plotly.graph_objects as go

fig = make_subplots(rows=2, cols=2, subplot_titles=('A', 'B', 'C', 'D'))
fig.add_trace(go.Scatter(x=[1, 2], y=[3, 4]), row=1, col=1)

Templates: Apply coordinated styling:

python
fig = px.scatter(df, x='x', y='y', template='plotly_dark')
# Built-in: plotly_white, plotly_dark, ggplot2, seaborn, simple_white

Customization: Control every aspect of appearance:

  • Colors (discrete sequences, continuous scales)
  • Fonts and text
  • Axes (ranges, ticks, grids)
  • Legends
  • Margins and sizing
  • Annotations and shapes

For complete layout and styling options, see reference/layouts-styling.md.

3. Interactivity

Built-in interactive features:

  • Hover tooltips with customizable data
  • Pan and zoom
  • Legend toggling
  • Box/lasso selection
  • Rangesliders for time series
  • Buttons and dropdowns
  • Animations
python
# Custom hover template
fig.update_traces(
    hovertemplate='<b>%{x}</b><br>Value: %{y:.2f}<extra></extra>'
)

# Add rangeslider
fig.update_xaxes(rangeslider_visible=True)

# Animations
fig = px.scatter(df, x='x', y='y', animation_frame='year')

For complete interactivity guide, see reference/export-interactivity.md.

4. Export Options

Interactive HTML:

python
fig.write_html('chart.html')                       # Full standalone
fig.write_html('chart.html', include_plotlyjs='cdn')  # Smaller file

Static Images (requires kaleido):

bash
uv pip install kaleido
python
fig.write_image('chart.png')   # PNG
fig.write_image('chart.pdf')   # PDF
fig.write_image('chart.svg')   # SVG

For complete export options, see reference/export-interactivity.md.

Common Workflows

Scientific Data Visualization
python
import plotly.express as px

# Scatter plot with trendline
fig = px.scatter(df, x='temperature', y='yield', trendline='ols')

# Heatmap from matrix
fig = px.imshow(correlation_matrix, text_auto=True, color_continuous_scale='RdBu')

# 3D surface plot
import plotly.graph_objects as go
fig = go.Figure(data=[go.Surface(z=z_data, x=x_data, y=y_data)])
Statistical Analysis
python
# Distribution comparison
fig = px.histogram(df, x='values', color='group', marginal='box', nbins=30)

# Box plot with all points
fig = px.box(df, x='category', y='value', points='all')

# Violin plot
fig = px.violin(df, x='group', y='measurement', box=True)
Time Series and Financial
python
# Time series with rangeslider
fig = px.line(df, x='date', y='price')
fig.update_xaxes(rangeslider_visible=True)

# Candlestick chart
import plotly.graph_objects as go
fig = go.Figure(data=[go.Candlestick(
    x=df['date'],
    open=df['open'],
    high=df['high'],
    low=df['low'],
    close=df['close']
)])
Multi-Plot Dashboards
python
from plotly.subplots import make_subplots
import plotly.graph_objects as go

fig = make_subplots(
    rows=2, cols=2,
    subplot_titles=('Scatter', 'Bar', 'Histogram', 'Box'),
    specs=[[{'type': 'scatter'}, {'type': 'bar'}],
           [{'type': 'histogram'}, {'type': 'box'}]]
)

fig.add_trace(go.Scatter(x=[1, 2, 3], y=[4, 5, 6]), row=1, col=1)
fig.add_trace(go.Bar(x=['A', 'B'], y=[1, 2]), row=1, col=2)
fig.add_trace(go.Histogram(x=data), row=2, col=1)
fig.add_trace(go.Box(y=data), row=2, col=2)

fig.update_layout(height=800, showlegend=False)

Integration with Dash

For interactive web applications, use Dash (Plotly's web app framework):

bash
uv pip install dash
python
import dash
from dash import dcc, html
import plotly.express as px

app = dash.Dash(__name__)

fig = px.scatter(df, x='x', y='y')

app.layout = html.Div([
    html.H1('Dashboard'),
    dcc.Graph(figure=fig)
])

app.run_server(debug=True)

Reference Files

Additional Resources

© davila7, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 5 other files in cli-tool/components/skills/scientific/plotly of davila7/claude-code-templates.

  • SKILL.md
  • reference/chart-types.md
  • reference/export-interactivity.md
  • reference/graph-objects.md
  • reference/layouts-styling.md
  • reference/plotly-express.md

Open the folder on GitHubat commit 4c82aba

Used in 14 other repositories

We found 29 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 14 other GitHub owners. This page covers the copy in davila7/claude-code-templates, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Plotly next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

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SeabornK-Dense-AI/scientific-agent-skills48k1 repos~3.4kAutomated safety check: NotesBSD-3-Clause
Data Visualizationw95/awesome-claude-corporate-skills2352 repos~2.8kAutomated safety check: PassMIT
Bio Data Visualization Flow And Transition PlotsGPTomics/bioSkills1.2k2 repos~2.9kAutomated safety check: PassMIT

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Works with

Categories

Questions about Plotly

What does Plotly do?

Interactive scientific and statistical data visualization library for Python. Plotly is an agent skill from davila7/claude-code-templates. Interactive scientific and statistical data visualization library for Python.

When should I use Plotly?

Plotly fits situations like: creating charts; visualizations including scatter plots; geographic maps; statistical distributions.

How do I install Plotly in Claude Code?

Run `npx skills add davila7/claude-code-templates --skill plotly -a claude-code`. Or copy the skill folder (cli-tool/components/skills/scientific/plotly in davila7/claude-code-templates) into .claude/skills/plotly in your project. Claude Code loads it when a task matches its description.

How do I install Plotly in Codex?

Run `npx skills add davila7/claude-code-templates --skill plotly -a codex`. Or copy the skill folder (cli-tool/components/skills/scientific/plotly in davila7/claude-code-templates) into .agents/skills/plotly in your project. Codex loads it when a task matches its description.

Can I use Plotly in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add davila7/claude-code-templates --skill plotly -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/plotly, .gemini/skills/plotly, .github/skills/plotly and .opencode/skills/plotly in your project.

What does Plotly need to run?

Going by SKILL.md and its folder, Plotly needs the command-line tools its instructions call (uv). Our summary lists: Python 3.

Does Plotly access the network?

SKILL.md names 2 domains. As links in the text: plotly.com and community.plotly.com. This is read from the text; nothing was executed.

Is Plotly safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Plotly use?

Plotly is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Plotly use?

About 1.8k tokens (SKILL.md is roughly 7.3k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Plotly?

Skills that share tags, products or a category with Plotly: CJK Font Setup for Plots (xjtulyc/MedgeClaw, 617 stars), Molecular Visualization 3dmol (jaechang-hits/SciAgent-Skills, 370 stars), Seaborn (K-Dense-AI/scientific-agent-skills, 48k stars) and Data Visualization (w95/awesome-claude-corporate-skills, 235 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Plotly?

davila7 (a GitHub user) maintains it in davila7/claude-code-templates, which has 32,432 GitHub stars. The repository holds 477 skills in this directory. The repository was last updated on October 7, 2026.

Source: davila7/claude-code-templates on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.