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Ict Trading Model

Community
carreypro
ict-trading-model

Analyze liquid markets with a strict ICT/SMC framework that combines multi-timeframe bias, liquidity sweeps, displacement, close-confirmed MSS/BOS, FVG/OB/Breaker/OTE retracements, premium-discount location, session timing, invalidation, targets, and risk-to-reward. Use for ICT chart reviews, live-market analysis, OHLCV scans, or validating a user's trade thesis. Return an auditable setup status and conditional plan; do not use for generic indicator analysis, order execution, or claims of proven institutional intent.

Overview

Publishercarreypro
Repositoryict-trading-model
Skill nameict-trading-model
Stars
67
Forks
21
Bundled files
5
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.

  • 5 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by carreypro on GitHub. Read the source before you install it.

Installation

Install the Ict Trading Model 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/carreypro/ict-trading-model/tree/main
  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/carreypro/ict-trading-model.git \
  .claude/skills/ict-trading-model
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Ict Trading Model 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 Ict Trading Model 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 Ict Trading Model 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.

ICT Trading Model

Turn ICT vocabulary into a falsifiable, candle-by-candle model. Treat ICT/SMC as a price-action framework, not a proven description of hidden institutional orders. Label observations, interpretations, and unknowns separately.

This skill is analysis-only. Never place or modify an order unless the user separately invokes an execution skill and explicitly authorizes that action.

Modes

  • Explain: define an ICT concept and show its bullish/bearish mirror.
  • Map: mark HTF bias, dealing range, external/internal liquidity, PD arrays, and active session on supplied or live candles.
  • Validate: test whether a claimed ICT setup meets every required gate.
  • Plan: after validation, produce a conditional entry, invalidation, target, R:R, and no-trade condition. Account sizing requires explicit risk inputs.

For concept definitions or manual chart annotation, read references/ict-model.md. For a plan, also read references/output-contract.md.

1. Establish data and clock

Confirm instrument, venue, candle source, holding horizon, and execution timeframe. For a live request, fetch fresh candles and state the query time. Never reuse a fixture, screenshot estimate, or cached price as current market data.

Use closed candles for confirmation. Report an open candle separately. Convert session timestamps with the IANA zone America/New_York; do not hard-code UTC offsets because daylight-saving time changes them.

Default timeframe stacks:

StyleBiasContextExecution
Intraday4H or 1H15m5m or 1m
Swing1D4H1H or 15m
Position1W1D4H

The highest timeframe sets the working bias, the middle timeframe maps the dealing range and liquidity, and the lowest timeframe supplies the trigger. When timeframes conflict, the result is developing or no-trade, not a forced signal.

2. Build the narrative before the trigger

Map, in this order:

  1. HTF order flow and the current dealing range;
  2. external liquidity: old highs/lows, equal highs/lows, prior day/week highs and lows, and session boundaries;
  3. internal liquidity and imbalances inside the range;
  4. premium, equilibrium, and discount;
  5. the next plausible liquidity draw and obstacles on the path;
  6. active New York-time session and nearby high-impact events.

Do not start with a low-timeframe FVG and invent the narrative afterward.

3. Apply the strict ICT setup gate

A confirmed setup needs all six gates. For a bullish setup; mirror every rule for bearish:

  1. Sell-side liquidity sweep: price trades below a meaningful prior low and rejects back above it. A simple breakout close below is not a bullish sweep.
  2. Bullish displacement: decisive expansion away from the sweep, with a large real body and a bullish FVG. A small bounce is insufficient.
  3. MSS: a closed candle breaks the relevant opposing swing high. A wick through the level is not enough.
  4. Dealing-range location: define the displacement range from the swept extreme to the MSS leg high; the entry PD array must be at equilibrium or in discount for a long, premium for a short.
  5. Retrace into a valid PD array: prefer the displacement FVG; OB, breaker, or OTE may add confluence but cannot replace sweep + displacement + MSS.
  6. Executable risk: stop beyond the sweep/structural invalidation, target opposing liquidity, and net R:R of at least 1:2 after costs.

Use scripts/ict_scan.py on OHLCV JSON to detect swing points, strict FVGs, liquidity sweeps, displacement, MSS, OTE overlap, retest state, and candidate R:R. The script is a consistency checker; visually verify meaningful levels and HTF context before accepting its output. Its mechanical_status is not the final skill status until the narrative, location, time, and data quality are manually verified.

4. Validate PD arrays precisely

  • FVG: a three-candle non-overlap. Bullish when candle 1 high is below candle 3 low; bearish when candle 1 low is above candle 3 high. Any wick overlap means no strict FVG.
  • OB: the final opposite candle before displacement that causes structure to break. Do not label every opposite candle an order block.
  • Breaker: a failed order block after a liquidity event, closed through and then retested from the other side. A generic support/resistance flip is not enough.
  • OTE: the 0.62-0.79 retracement of a defined impulse, with 0.705 as the center. OTE is confluence, not a standalone entry.
  • IFVG: an FVG closed through with displacement and later respected from the opposite side. A wick through alone does not invert it.

When a concept cannot be proven from the available candles, mark it unverified; never upgrade it because the trade idea looks attractive.

5. Respect time and event filters

Express all windows in New York time and state the date:

  • London focus: 02:00-05:00;
  • New York opening focus: 07:00-10:00;
  • Silver Bullet focus: 10:00-11:00;
  • lunch 12:00-13:30 is normally no-trade;
  • afternoon 13:30-16:00 is conditional on a clear trend-day narrative.

Time is a filter, not proof. A setup outside the preferred windows can be reported, but confidence is lower. If high-impact news is imminent or its schedule is unavailable, state the uncertainty and do not call the setup high-confidence.

6. Classify, do not overclaim

Return exactly one status:

  • confirmed: every gate is evidenced on closed candles and R:R passes;
  • developing: the narrative is valid but a required gate or retrace is still pending;
  • invalidated: price has crossed the structural invalidation or contradicted the HTF premise;
  • no-trade: evidence is conflicting, late, stale, incomplete, or below the minimum R:R.

If the user requests a direction that contradicts the evidence, show the conflict and the condition that would restore that direction. Do not force a matching plan.

7. Present auditable evidence

Include candle timestamps and prices for the sweep, displacement/FVG, MSS, retrace, invalidation, and target. Separate:

  • observed: directly present in candles or market data;
  • derived: swing, FVG, range midpoint, OTE, R:R;
  • interpretive: bias, narrative, and likely liquidity draw;
  • missing: unavailable HTF, session, news, spread, or fee inputs.

End with a short educational-risk notice. ICT labels are hypotheses and do not guarantee price behavior or institutional participation.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Ict Trading Model AI skill do?

Analyze liquid markets with a strict ICT/SMC framework that combines multi-timeframe bias, liquidity sweeps, displacement, close-confirmed MSS/BOS, FVG/OB/Breaker/OTE retracements, premium-discount location, session timing, invalidation, targets, and risk-to-reward. Use for ICT chart reviews, live-market analysis, OHLCV scans, or validating a user's trade thesis. Return an auditable setup status and conditional plan; do not use for generic indicator analysis, order execution, or claims of proven institutional intent.

Why use Ict Trading Model on TypingMind?

Because you install it once and use it with any model. Ict Trading Model 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 Ict Trading Model in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/carreypro/ict-trading-model/tree/main. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Ict Trading Model?

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 Ict Trading Model?

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

Is the Ict Trading Model AI skill free?

Yes. It is published on GitHub by carreypro 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.

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