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indicator-dashboard指示器仪表板

Agent Skill

indicator-dashboard 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

3,768

周安装

157

GitHub Stars

8

下载量

1,256
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:indicator-dashboard(指示器仪表板)
来源仓库:https://github.com/marketcalls/openalgo-indicator-skills
仓库路径:skills/indicator-dashboard
安装命令:
npx skills add https://github.com/marketcalls/openalgo-indicator-skills --skill indicator-dashboard
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/marketcalls/openalgo-indicator-skills --skill indicator-dashboard

简介

indicator-dashboard 用于查找、检索和筛选相关信息。

  • 适合在 Codex、Claude、Cursor、Gemini CLI 中根据关键词、任务场景或来源线索快速定位候选结果。
  • 通过 npx skills add 命令从指定 GitHub 仓库安装并使用。
  • 安装前需确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写操作。
  • 适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

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.

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="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

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

37.92%
按下载量换算476

Claude

32.86%
按下载量换算413

Cursor

16.78%
按下载量换算211

Gemini CLI

9.49%
按下载量换算119

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

操作浏览器

该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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