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multi-timeframe-analysis多时间框架分析

Agent Skill

multi-timeframe-analysis 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。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

635

周安装

27

GitHub Stars

14

下载量

222
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:multi-timeframe-analysis(多时间框架分析)
来源仓库:https://github.com/bhala-srinivash/nse-trading-skills
仓库路径:skills/multi-timeframe-analysis
安装命令:
npx skills add https://github.com/bhala-srinivash/nse-trading-skills --skill multi-timeframe-analysis
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/bhala-srinivash/nse-trading-skills --skill multi-timeframe-analysis

简介

用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息。

  • 适合在 Codex、Claude、Cursor、Gemini CLI 中围绕仓库状态、代码变更或协作事项进行整理。
  • 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。
  • 使用时需注意 API 调用频率限制和数据隐私边界。

SKILL.md

Multi-Timeframe Analysis

Higher timeframes set the direction. Lower timeframes refine the entry. Never trade against the higher timeframe trend unless you have very strong reasons.

The 3-Screen Method

ScreenTimeframePurposeWhat to Look For
Screen 1WeeklyTrend biasPrimary trend, major S/R, 200-week MA
Screen 2DailySetupPattern formation, indicator signals, entry zone
Screen 34H / 1HEntry timingPrecise entry price, tight stop placement

How to use it:

  1. Weekly decides direction — only take trades in the weekly trend's direction
  2. Daily identifies the setup — pullback to support in uptrend, rally to resistance in downtrend
  3. Hourly/4H times the entry — wait for the lower TF to confirm reversal in your direction

Prerequisites

No dependencies required. Framework applies to any timeframe data. Enhanced with Groww MCP (multi-interval candles) or yfinance (pip install yfinance) for weekly/monthly history.

Fetching Multi-TF Data

When data tools are available:

Weekly:  fetch_historical_candle_data with interval=1w
Daily:   fetch_historical_candle_data with interval=1d
Hourly:  fetch_historical_candle_data with interval=1h (limited to ~30 days)

For weekly indicators via yfinance: yf.download("SYMBOL.NS", period="2y", interval="1wk")

Screen 1: Weekly Analysis

Check these on the weekly chart:

  • Trend: Series of higher highs/lows (up) or lower highs/lows (down)?
  • Position vs MAs: Price relative to 20W and 50W SMA
  • RSI(14) weekly: Above 50 = bullish bias, below 50 = bearish bias
  • Major S/R: Horizontal levels with multiple weekly touches
  • Volume trend: Rising into the trend direction = healthy

Weekly verdict: Bullish / Bearish / Neutral — this sets your trading bias.

Screen 2: Daily Analysis

With the weekly bias established:

  • Look for setups that align: Pullbacks to buy in uptrend, rallies to sell in downtrend
  • Pattern identification: Flags, wedges, double bottoms/tops, breakouts
  • Indicator signals: RSI, MACD, Bollinger on daily
  • Volume: Confirmation of the setup (declining volume on pullback = healthy)

Daily verdict: Setup present / No setup / Counter-trend setup (risky)

Screen 3: Entry Timeframe (4H / 1H)

Once weekly bias + daily setup align:

  • Wait for lower TF confirmation: A candlestick reversal pattern, RSI bounce, or MACD cross
  • Place entry: At the confirmation signal
  • Set stop: Based on lower TF structure (tighter = better R:R)
  • Target: From daily/weekly levels

Confluence Scoring

Award 1 point for each alignment. This keeps you honest about setup quality.

FactorPoint
Weekly trend agrees with trade direction+1
Daily shows valid setup pattern+1
RSI supports on daily timeframe+1
MACD supports on daily timeframe+1
Key S/R level provides clear stop or target+1
Volume confirms the move+1
ScoreAction
5-6Strong setup — full position size
4Good setup — full position size
3Marginal — half position size
2Weak — skip or paper trade only
0-1No setup — do not trade

Common Mistakes

  • Trading against the weekly trend hoping for a reversal — the weekly trend wins most of the time
  • Using only one timeframe — you miss context and enter with poor timing
  • Forcing alignment — if timeframes disagree, the answer is "no trade" not "trade anyway"

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

37.86%
按下载量换算84

Claude

29.09%
按下载量换算65

Cursor

17.92%
按下载量换算40

Gemini CLI

9.3%
按下载量换算21

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

external-service

该 Skill 可能调用第三方服务、云服务或外部模型 API,使用前需要确认账号、额度、数据发送范围和服务条款。

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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