chart

Chart — Project-Based Interactive Charting

Generate interactive chart pages with Apache ECharts. Each chart lives in a dedicated project folder under output/chart-html/, making it easy to reuse and iterate.

When to Use

Any time the user wants a visual chart: price charts, comparisons, dashboards, business analytics, etc.

Architecture

ECharts (CDN) for rendering
ECharts native export (getDataURL) + canvas merge for reliable PNG output
Project-based storage: one folder per chart project
No gallery mode: all artifacts stay in the project folder

Project Structure (Required)

Each chart project should follow:

output/chart-html/
  <project-name>/
    index.html        # chart page
    generate.py       # generation script (for reproducibility)
    README.md         # title / description / data source notes
    data.json         # data snapshot
    screenshot.png    # saved image

Example folder name: btc-90d-20260401

Workflow

Step 1: Pick template or custom layout

Available templates:

Template	Best for
`line.html`	Time-series trends, multi-series comparisons
`bar.html`	Category comparisons, rankings
`pie.html`	Composition / share breakdown
`candlestick.html`	OHLCV price charts
`scatter.html`	Correlation, distribution
`dashboard.html`	KPI cards + 2×2 multi-chart grid
`radar.html`	Multi-dimension scoring
`heatmap.html`	Matrix / calendar intensity
`dual-axis.html`	Two series with very different scales (e.g. market cap vs stablecoin supply) — left and right Y axes, each with its own label color
`multi-panel.html`	Stacked panels sharing one X axis (e.g. price + volume + RSI) — single ECharts instance, tooltip/zoom synced across all panels
`waterfall.html`	Incremental contribution breakdown (e.g. P&L attribution, budget variance) — positive/negative bars stacked on a floating base

Step 2: Create project folder

Use create_project(name, description, data_sources) from scripts/build_chart.py.

Step 3: Build and save chart page

Use either:

build_chart(template_name, ...)
build_chart_custom(...)

Then save as index.html in the project folder:

save_chart(html, project_dir=project_dir)

Step 4: Save reproducible assets

Also save:

save_generate_script(script_content, project_dir) → generate.py
save_data(data, project_dir) → data.json
project README is created by create_project(...)

Step 5: Serve preview

Use project-root serving (recommended):

preview_serve(
  title="Chart Preview",

Then open: /preview/<id>/<project-name>/index.html

Important behavior in v3.0.1:

chart_server.py now rewrites preview-prefixed static paths internally (/preview/<id>/... → /...) before filesystem lookup.
This guarantees the preview iframe resolves the real project index.html instead of falling back to root directory listing.
Keep project pages under output/chart-html/<project>/index.html (do not serve output/chart-html directly as a static preview without chart_server.py).

Step 6: Export image

Two modes:

User wants web page + image: click "💾 Save Image" in page toolbar, saves to current project as screenshot.png
User wants image only: call screenshot_chart(project_dir) (Playwright) and send screenshot.png directly

Every chart page must include these buttons:

Do not include gallery entry.

Key Files

File	Purpose
`skills/chart/scripts/base-styles.css`	Base dark theme CSS
`skills/chart/scripts/base-export.js`	Export helpers: download/copy/save-to-project
`skills/chart/scripts/build_chart.py`	Project creation, HTML build, data/script save, screenshot
`skills/chart/scripts/chart_server.py`	Static server + `/save-chart` API
`skills/chart/templates/*.html`	Reusable chart templates
`output/chart-html/<project>/*`	All generated chart artifacts

Notes

Embed data directly in HTML (const DATA = ...) to avoid iframe CORS issues.
For multi-chart pages, register all chart instances in window.CHART_INSTANCES.
Use meaningful project names (topic-range-date) for easy lookup.

Chart — Project-Based Interactive Charting

Generate interactive chart pages with Apache ECharts. Each chart lives in a dedicated project folder under output/chart-html/, making it easy to reuse and iterate.

When to Use

Any time the user wants a visual chart: price charts, comparisons, dashboards, business analytics, etc.

Architecture

ECharts (CDN) for rendering
ECharts native export (getDataURL) + canvas merge for reliable PNG output
Project-based storage: one folder per chart project
No gallery mode: all artifacts stay in the project folder

Project Structure (Required)

Each chart project should follow:

output/chart-html/
  <project-name>/
    index.html        # chart page
    generate.py       # generation script (for reproducibility)
    README.md         # title / description / data source notes
    data.json         # data snapshot
    screenshot.png    # saved image

Example folder name: btc-90d-20260401

Workflow

Step 1: Pick template or custom layout

Available templates:

Template	Best for
`line.html`	Time-series trends, multi-series comparisons
`bar.html`	Category comparisons, rankings
`pie.html`	Composition / share breakdown
`candlestick.html`	OHLCV price charts
`scatter.html`	Correlation, distribution
`dashboard.html`	KPI cards + 2×2 multi-chart grid
`radar.html`	Multi-dimension scoring
`heatmap.html`	Matrix / calendar intensity
`dual-axis.html`	Two series with very different scales (e.g. market cap vs stablecoin supply) — left and right Y axes, each with its own label color
`multi-panel.html`	Stacked panels sharing one X axis (e.g. price + volume + RSI) — single ECharts instance, tooltip/zoom synced across all panels
`waterfall.html`	Incremental contribution breakdown (e.g. P&L attribution, budget variance) — positive/negative bars stacked on a floating base

Step 2: Create project folder

Use create_project(name, description, data_sources) from scripts/build_chart.py.

Step 3: Build and save chart page

Use either:

build_chart(template_name, ...)
build_chart_custom(...)

Then save as index.html in the project folder:

save_chart(html, project_dir=project_dir)

Step 4: Save reproducible assets

Also save:

save_generate_script(script_content, project_dir) → generate.py
save_data(data, project_dir) → data.json
project README is created by create_project(...)

Step 5: Serve preview

Use project-root serving (recommended):

preview_serve(
  title="Chart Preview",

Then open: /preview/<id>/<project-name>/index.html

Important behavior in v3.0.1:

chart_server.py now rewrites preview-prefixed static paths internally (/preview/<id>/... → /...) before filesystem lookup.
This guarantees the preview iframe resolves the real project index.html instead of falling back to root directory listing.
Keep project pages under output/chart-html/<project>/index.html (do not serve output/chart-html directly as a static preview without chart_server.py).

Step 6: Export image

Two modes:

User wants web page + image: click "💾 Save Image" in page toolbar, saves to current project as screenshot.png
User wants image only: call screenshot_chart(project_dir) (Playwright) and send screenshot.png directly

Every chart page must include these buttons:

Do not include gallery entry.

Key Files

File	Purpose
`skills/chart/scripts/base-styles.css`	Base dark theme CSS
`skills/chart/scripts/base-export.js`	Export helpers: download/copy/save-to-project
`skills/chart/scripts/build_chart.py`	Project creation, HTML build, data/script save, screenshot
`skills/chart/scripts/chart_server.py`	Static server + `/save-chart` API
`skills/chart/templates/*.html`	Reusable chart templates
`output/chart-html/<project>/*`	All generated chart artifacts

Notes

Embed data directly in HTML (const DATA = ...) to avoid iframe CORS issues.
For multi-chart pages, register all chart instances in window.CHART_INSTANCES.
Use meaningful project names (topic-range-date) for easy lookup.

Documentation

Documentation

Chart — Project-Based Interactive Charting

When to Use

Architecture

Project Structure (Required)

Workflow

Step 1: Pick template or custom layout

Step 2: Create project folder

Step 3: Build and save chart page

Step 4: Save reproducible assets

Step 5: Serve preview

Step 6: Export image

Key Files

Notes

Documentation

chart

Documentation

Chart — Project-Based Interactive Charting

When to Use

Architecture

Project Structure (Required)

Workflow

Step 1: Pick template or custom layout

Step 2: Create project folder

Step 3: Build and save chart page

Step 4: Save reproducible assets

Step 5: Serve preview

Step 6: Export image

Key Files

Notes

chart

Documentation

Documentation

Chart — Project-Based Interactive Charting

When to Use

Architecture

Project Structure (Required)

Workflow

Step 1: Pick template or custom layout

Step 2: Create project folder

Step 3: Build and save chart page

Step 4: Save reproducible assets

Step 5: Serve preview

Step 6: Export image

Toolbar Requirements

Key Files

Notes

Documentation

chart

Documentation

Chart — Project-Based Interactive Charting

When to Use

Architecture

Project Structure (Required)

Workflow

Step 1: Pick template or custom layout

Step 2: Create project folder

Step 3: Build and save chart page

Step 4: Save reproducible assets

Step 5: Serve preview

Step 6: Export image

Toolbar Requirements

Key Files

Notes