Indicator Dashboard

This builds interactive technical analysis dashboards using either Plotly Dash or Streamlit, which is nice since you can pick whichever framework you're more comfortable with. You get single symbol views with configurable indicators, multi-timeframe grids for confluence analysis, and scanner dashboards that monitor watchlists. Everything comes with dark themes, auto-refresh, and the usual exchange/interval selectors. The skill reads from template files and creates project directories on demand, so you're not writing boilerplate layout code. Most useful when you want a quick visual interface for indicator combinations without manually coding all the callbacks and chart formatting. The multi-timeframe view is probably the most interesting one since it surfaces divergences across time periods automatically.

skills.sh installs: 589
GitHub stars: 21
last updated: Aug 21, 2026

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Install

$ npx -y skills add marketcalls/openalgo-indicator-skills --skill indicator-dashboard --agent claude-code

Installs into .claude/skills of the current project.

Files

Create a web dashboard for interactive technical analysis using Plotly Dash or Streamlit.

Arguments

Parse $ARGUMENTS as: type symbol

$0 = dashboard type. Default: single
- Dash types: single, multi-symbol, multi-timeframe, scanner-dashboard
- Streamlit types: streamlit-single, streamlit-multi, streamlit-scanner
$1 = symbol (e.g., SBIN, RELIANCE). Default: SBIN

If no arguments, ask the user what kind of dashboard they want and whether they prefer Dash or Streamlit.

Framework choice: Plotly Dash is the default. Build a Streamlit app ONLY when the user explicitly asks for Streamlit (says "streamlit" or picks a streamlit-* type). Never silently switch frameworks.

Instructions

Read the indicator-expert rules, especially:
- rules/dashboard-patterns.md — Dash app patterns
- rules/streamlit-patterns.md — Streamlit app patterns
- rules/plotting.md — Chart patterns
- rules/data-fetching.md — Data loading
Create dashboards/{dashboard_name}/ directory (on-demand)
Create app.py in dashboards/{dashboard_name}/
Use the matching template from rules/assets/