Multi Timeframe Analysis logo

Multi Timeframe Analysis

Community
Bhala-Srinivash
multi-timeframe-analysis

Multi-timeframe analysis using the 3-screen method for NSE/BSE equities. Higher timeframe sets bias, primary timeframe identifies setup, lower timeframe times the entry. Includes confluence scoring system. Use when the user asks: "what's the weekly trend", "daily vs weekly", "multi-timeframe check", "higher timeframe analysis", "3-screen analysis", "trend on different timeframes", "weekly bias for [stock]", or any question about analyzing a stock across multiple timeframes.

Overview

PublisherBhala-Srinivash
Repositorynse-trading-skills
Skill namemulti-timeframe-analysis
Stars
59
Forks
25
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by Bhala-Srinivash on GitHub. Read the source before you install it.

Installation

Install the Multi Timeframe Analysis AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/Bhala-Srinivash/nse-trading-skills/tree/master/multi-timeframe-analysis
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/Bhala-Srinivash/nse-trading-skills.git /tmp/nse-trading-skills
mkdir -p .claude/skills
cp -r /tmp/nse-trading-skills/multi-timeframe-analysis .claude/skills/multi-timeframe-analysis
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Multi Timeframe Analysis in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Multi Timeframe Analysis on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Multi Timeframe Analysis is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

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"

Frequently asked questions

What does the Multi Timeframe Analysis AI skill do?

Multi-timeframe analysis using the 3-screen method for NSE/BSE equities. Higher timeframe sets bias, primary timeframe identifies setup, lower timeframe times the entry. Includes confluence scoring system. Use when the user asks: "what's the weekly trend", "daily vs weekly", "multi-timeframe check", "higher timeframe analysis", "3-screen analysis", "trend on different timeframes", "weekly bias for [stock]", or any question about analyzing a stock across multiple timeframes.

Why use Multi Timeframe Analysis on TypingMind?

Because you install it once and use it with any model. Multi Timeframe Analysis is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Multi Timeframe Analysis in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Bhala-Srinivash/nse-trading-skills/tree/master/multi-timeframe-analysis. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Multi Timeframe Analysis?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Multi Timeframe Analysis?

As many as you like. As long as a model supports skills, you can use Multi Timeframe Analysis with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Multi Timeframe Analysis AI skill free?

Yes. It is published on GitHub by Bhala-Srinivash under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Set up your own AI workspace now

Get notified about new features and future giveaways by subscribing to our newsletter 👇