Market Session Tracker logo

Market Session Tracker

Organization
kansoku-trade
market-session-tracker

Use when monitoring stocks/ETFs/indices across pre-market, open, intraday, or close — especially when the user is reading session action live and may revise their take as it unfolds. Triggers include 盘前/盘中/收盘 sessions, multi-symbol watchlists (e.g. MU/TSM/SMH semi tracking), user observations like "突破"/"冲高"/"回调"/"假突破", capital flow checks, market temperature checks, semi/AI/memory plays, and any request that bundles a position context with a live read.

Overview

Publisherkansoku-trade
Repositorykansoku
Skill namemarket-session-tracker
Stars
329
Forks
40
Bundled files
3
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.

  • 3 bundled files

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

  • Open source

    Published by kansoku-trade on GitHub. Read the source before you install it.

Installation

Install the Market Session Tracker 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/kansoku-trade/kansoku/tree/main/.claude/skills/market-session-tracker
  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/kansoku-trade/kansoku.git /tmp/kansoku
mkdir -p .claude/skills
cp -r /tmp/kansoku/.claude/skills/market-session-tracker .claude/skills/market-session-tracker
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Market Session Tracker 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 Market Session Tracker 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 Market Session Tracker 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.

Market Session Tracker

Real-time US-market analysis pattern. Sits on top of longbridge-quote, longbridge-kline, longbridge-capital-flow, longbridge-market-temp — adds orchestration, breakout verification, distribution detection, tier classification, and revision discipline.

Standard symbol sets

ThemeSymbols
Semi / memoryMU.US, TSM.US, DRAM.US (Roundhill Memory ETF), SMH.US, SOXX.US
IndicesQQQ.US, SPY.US, DIA.US, IWM.US
Vol / risk-offVXX.US, UVXY.US, TLT.US, GLD.US

.SOX.US is unavailable on Longbridge — use SMH/SOXX ETF proxies.

Seven protocols

0. Trump-feed sweep (pre-cash) — before any pre-market read, run python3 .claude/skills/trump-truth-monitor/scripts/fetch.py --hours 14. Any high-tier post touching watchlist sectors (tariff_trade / semi_tech / energy / fed_macro / geopolitical) goes into the session report as a candidate explanation for any gap, before running quote-based exuberance math. Skip when the watchlist has no policy-exposed names. See trump-truth-monitor skill for tier grading.

1. Pre-market verification — compute pre vol % of prev day full vol, and pre high % over prev_close. Flag exuberance when pre vol > 5% of prev day and pre high > prev_close × 1.07.

2. Failed-breakout 6-signal stack — count how many fire in the cash session:

  1. Pre-market high NOT touched in first 30 min of cash
  2. New intraday high breaks → price falls back below the broken level within minutes
  3. Volume does NOT expand at the breakout
  4. Sector ETF (SMH/SOXX) does NOT confirm by going green
  5. Leader stock (MU for memory; TSM for foundry; NVDA for AI) does NOT make new high
  6. Capital flow: all 3 buckets net selling

≥ 4 signals fired = failed breakout / distribution. Name the tier (§5).

3. Capital flow triple-bucket — longbridge capital <SYM> --format json. Net = capital_in − capital_out for each of large / medium / small. All 3 net out = textbook distribution. Use --flow for accelerating-outflow detection.

4. Cross-asset sentiment matrix

PatternInterpretation
DIA > SPY > QQQ + VXX downRotation (defensive), not panic
VXX up + GLD up + TLT upTrue risk-off
Sector red + SPY flat + VXX downIsolated distribution
HK/CN valuation ≥ 80 + sentiment ≤ 35Known-bubble (overvalued, retail knows)

5. Pullback tier classification

TierTriggers
1 震荡Stock −2% from intraday high; closes green
2 实质回调Stock −5% from peak; sector ETF turns red
3 板块下跌Sector −3%+; broad indices flat-to-red
4 风险传染SPY −1%+; VXX +5%+; defensives also fall

Always name the tier explicitly — never vague "weakening".

6. Scenario probabilities — always 3 scenarios (Bull / Base / Bear) with explicit % (sum=100) and trigger conditions. Mark probabilities as subjective. Revise as data flows with timestamps: 09:30 初判 → 09:54 修正 → 09:56 再修正.

7. Thesis revision discipline — when user says "突破"/"冲高"/"回调":

  1. Re-pull live quote + intraday minute tail — do NOT auto-agree
  2. Check cash intraday high vs pre-market high vs prior intraday high
  3. Distinguish: true breakout (new high > pre high, holds 5+ min) vs partial (breaks prior intra high but not pre high) vs recovery (only bounces from intra low)
  4. If data contradicts user, disagree with evidence

Output format (each snapshot)

  • Time (ET) — always
  • Symbol table — last, change%, intra high/low, vs pre high, vol
  • Key signal (one sentence)
  • Tier (if pullback context)
  • Next watch levels (explicit prices, not "around X")
  • Source: 长桥证券 · Disclaimer: ⚠️ 仅供参考,不构成投资建议

Session report logging

After a session, write a structured log using templates/session-report.md in this skill. Default path: ~/git/trade/journal/YYYY-MM-DD-<theme>.md (a dedicated git repo; journal/ avoids the logs global-gitignore collision). Captures pre-market verdict, opening behavior, tier evolution, thesis revisions, capital flow, cross-asset sentiment, end-of-day outcome, and lessons.

Optional: position context

When user provides positions or asks via longbridge positions:

  • Show symbol, qty, avg cost, current price, unrealized P&L, % of book
  • Cross-reference which positions are exposed to the current move
  • Do NOT recommend buy/sell — defer to user

Anti-patterns

  • ❌ Auto-confirming user's directional read (re-pull data first)
  • ❌ Calling a cash bounce a "breakout" without checking pre-market high
  • ❌ Single-point price prediction (use 3 scenarios)
  • ❌ Vague "weak/strong" — use tier classification
  • ❌ Conflating sector weakness with systemic (check VXX/GLD/SPY)
  • ❌ Calling trend in first 5 min (wait for 30-min K)

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 Market Session Tracker AI skill do?

Use when monitoring stocks/ETFs/indices across pre-market, open, intraday, or close — especially when the user is reading session action live and may revise their take as it unfolds. Triggers include 盘前/盘中/收盘 sessions, multi-symbol watchlists (e.g. MU/TSM/SMH semi tracking), user observations like "突破"/"冲高"/"回调"/"假突破", capital flow checks, market temperature checks, semi/AI/memory plays, and any request that bundles a position context with a live read.

Why use Market Session Tracker on TypingMind?

Because you install it once and use it with any model. Market Session Tracker 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 Market Session Tracker in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/kansoku-trade/kansoku/tree/main/.claude/skills/market-session-tracker. 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 Market Session Tracker?

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 Market Session Tracker?

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

Is the Market Session Tracker AI skill free?

It is published on GitHub by kansoku-trade. Check the repository for licensing terms. 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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