marketcalls/openalgo-indicator-skills

indicator-dashboard

Build a web dashboard for technical indicator analysis using Plotly Dash or Streamlit. Supports single-symbol, multi-symbol, and multi-timeframe layouts with real-time refresh.

First seen Feb 28, 2026

Installation

$ npx skills add marketcalls/openalgo-indicator-skills --skill indicator-dashboard

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More details

Agent compatibility

Declared targets from SKILL.md / docs. Unmarked agents are not listed — the skill may still install via the CLI.

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Repository health

Stars 14
License MIT
Default branch master
Open issues 0
Status Active

Skill metadata

Parsed from SKILL.md frontmatter.

Allowed toolsRead, Write, Edit, Bash, Glob, Grep, AskUserQuestion

Package contents

Files included with this skill beyond the listing page.

  • skill md SKILL.md 4,726 B
  • docs SUMMARY.md 200 B

History

  1. First seen on skills.sh
  2. First recorded snapshot · 475 installs

SKILL.md

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

  1. Create dashboards/{dashboard_name}/ directory (on-demand)
  2. Create app.py in dashboards/{dashboard_name}/
  3. 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="plotlydark", xaxistype="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