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Indicator Dashboard

  • 391 installs
  • 13 repo stars
  • Updated June 12, 2026
  • marketcalls/openalgo-indicator-skills

indicator-dashboard is a Claude Code skill that builds OpenAlgo indicator dashboards visualizing signals, timeframes, watchlists, and alerts for developers who monitor multiple trading symbols in one view.

About

indicator-dashboard is an agent skill from marketcalls/openalgo-indicator-skills that guides developers through assembling OpenAlgo indicator dashboards. The skill wires together signal panels, multi-timeframe views, symbol watchlists, and alert rules so traders can monitor many instruments without jumping between separate screens. It assumes OpenAlgo is already connected to market data and indicator computations, then focuses on dashboard structure, layout, and alert surfacing. Developers reach for indicator-dashboard when they need a consolidated monitoring surface for live or backtested signals rather than one-off chart scripts. The workflow produces dashboard configuration, watchlist definitions, and alert hooks ready to run against OpenAlgo endpoints.

  • Multi-symbol watchlist layouts
  • Signal and timeframe visualization
  • Alert and status panels
  • Responsive trader-focused UI
  • OpenAlgo data binding patterns

Indicator Dashboard by the numbers

  • 391 all-time installs (skills.sh)
  • +22 installs in the week ending Aug 2, 2026 (Skillselion tracking)
  • Ranked #272 of 1,106 Finance & Trading skills by installs in the Skillselion catalog
  • Data as of Aug 2, 2026 (Skillselion catalog sync)
npx skills add https://github.com/marketcalls/openalgo-indicator-skills --skill indicator-dashboard

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Listed on Skillselion
Installs391
repo stars13
Last updatedJune 12, 2026
Repositorymarketcalls/openalgo-indicator-skills

How do you build multi-symbol OpenAlgo indicator dashboards?

Build OpenAlgo indicator dashboards that visualize signals, timeframes, watchlists, and alerts for traders monitoring multiple symbols.

Who is it for?

Developers already streaming OpenAlgo indicators who need a unified monitoring dashboard across symbols and timeframes.

Skip if: Skip indicator-dashboard when you only need a single-symbol chart or have not connected OpenAlgo feeds and indicator jobs yet.

When should I use this skill?

The user asks to build, layout, or extend an OpenAlgo indicator dashboard with watchlists, alerts, or multi-timeframe views.

What you get

OpenAlgo dashboard layout, watchlist config, timeframe views, and alert rule definitions.

  • Dashboard layout config
  • Watchlist and alert definitions

Files

SKILL.mdMarkdownGitHub ↗

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

1. 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

2. Create dashboards/{dashboard_name}/ directory (on-demand) 3. Create app.py in dashboards/{dashboard_name}/ 4. Use the matching template from rules/assets/

Dashboard Requirements

All dashboards must include:

  • Dark theme: Dash uses dbc.themes.DARKLY; Streamlit uses [theme] base = "dark" or CSS injection
  • Symbol input: Text input or dropdown for symbol selection
  • Exchange selector: NSE, BSE, NFO, NSE_INDEX
  • Interval selector: 1m, 5m, 15m, 1h, D
  • Indicator selectors: Checkboxes/multiselect for overlay and subplot indicators
  • Interactive chart: Plotly chart with template="plotly_dark", xaxis_type="category"
  • Stats display: Key metrics (LTP, Change, Volume, indicator values)
  • Auto-refresh: Dash uses dcc.Interval; Streamlit uses st.rerun() with time.sleep()
  • Load `.env` from project root via find_dotenv()

Dash Dashboard Types

single — Single Symbol Dashboard (Dash)
  • One symbol with configurable indicators
  • Overlays: EMA, SMA, Bollinger, Supertrend, Ichimoku (checkboxes)
  • Subplots: RSI, MACD, Stochastic, Volume, ADX, OBV (checkboxes)
  • Stats panel: LTP, day change, volume, selected indicator values
  • Template: rules/assets/dashboard_basic/app.py
multi-symbol — Multi-Symbol Watchlist (Dash)
  • 4-6 symbols in a grid layout
  • Each cell shows candlestick + one overlay indicator
  • Bottom row: RSI comparison across all symbols
  • Symbol list editable via input
multi-timeframe — MTF Analysis (Dash)
  • 4-panel grid: 5m, 15m, 1h, D for same symbol
  • Same indicators computed on each timeframe
  • Confluence summary: "3/4 timeframes bullish"
  • Template: rules/assets/dashboard_multi/app.py
scanner-dashboard — Live Scanner (Dash)
  • Watchlist of 10+ symbols
  • Table showing: Symbol, LTP, RSI, EMA trend, Signal
  • Color-coded rows (green=bullish, red=bearish)
  • Click symbol to show detailed chart
  • Auto-refresh every 30 seconds

Streamlit Dashboard Types

streamlit-single — Single Symbol Dashboard (Streamlit)
  • Sidebar: symbol, exchange, interval, overlay/subplot multiselect
  • st.plotly_chart() for interactive charts
  • st.metric() for LTP, Change, RSI, EMA stats
  • Auto-refresh via checkbox + st.rerun()
  • Template: rules/assets/streamlit_basic/app.py
streamlit-multi — MTF Analysis (Streamlit)
  • 2x2 grid via st.columns(2) for 4 timeframes
  • Candlestick + EMA overlay per timeframe
  • Confluence summary with st.success()/st.error()/st.warning()
  • st.metric() cards for each timeframe trend
  • Template: rules/assets/streamlit_multi/app.py
streamlit-scanner — Scanner Dashboard (Streamlit)
  • Sidebar: scan type selector, run button
  • st.progress() during scan
  • st.dataframe() for results table
  • st.download_button() for CSV export

Running the Dashboard

After creating the app, provide instructions:

Dash:

cd dashboards/{dashboard_name}
python app.py
# Open http://127.0.0.1:8050 in browser

Streamlit:

cd dashboards/{dashboard_name}
streamlit run app.py
# Open http://localhost:8501 in browser

Example Usage

/indicator-dashboard single SBIN /indicator-dashboard multi-timeframe RELIANCE /indicator-dashboard scanner-dashboard /indicator-dashboard streamlit-single SBIN /indicator-dashboard streamlit-multi RELIANCE /indicator-dashboard streamlit-scanner

Related skills

How it compares

Pick indicator-dashboard over live-feed when the goal is dashboard layout and alerts rather than WebSocket tick ingestion.

FAQ

What does indicator-dashboard build on OpenAlgo?

indicator-dashboard assembles OpenAlgo indicator dashboards that combine signal panels, timeframe views, symbol watchlists, and alert rules. Developers use it to monitor multiple symbols from one consolidated trading surface.

When should developers use indicator-dashboard?

indicator-dashboard fits after OpenAlgo feeds and indicator logic exist and you need a multi-symbol monitoring UI. Use it when alerts, watchlists, and timeframe panels must live in one dashboard instead of separate scripts.

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