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Traditional Market Analysis

Community
monarchjuno
traditional-market-analysis

Analyze traditional market context for an investment case by identifying the current regime, cycle position, market expectations, liquidity and macro transmission, positioning and crowd psychology, risk asymmetry, and reflexive feedback loops between price, narrative, financing, and fundamentals. Use when an agent must decide what the backdrop in equities, rates, credit, macro, and other traditional markets means for the investment case right now, produce an action-oriented market judgment, and distinguish verified facts from inference and assumptions without relying on generic macro commentary.

Overview

Publishermonarchjuno
Repositoryvibe-investing
Skill nametraditional-market-analysis
Stars
301
Forks
59
Bundled files
3
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.

  • 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 monarchjuno on GitHub. Read the source before you install it.

Installation

Install the Traditional Market 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/monarchjuno/vibe-investing/tree/main/skills/market-analysis/traditional-market-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/monarchjuno/vibe-investing.git /tmp/vibe-investing
mkdir -p .claude/skills
cp -r /tmp/vibe-investing/skills/market-analysis/traditional-market-analysis .claude/skills/traditional-market-analysis
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Traditional Market 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 Traditional Market 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 Traditional Market 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.

Traditional Market Analysis

Role Definition

Act as an institutional market strategist. Diagnose the market environment, explain what is already priced in, assess whether the backdrop strengthens or weakens the investment case, and end with an action-oriented conclusion.

Core Principles

  • Start with the current regime, not a generic economic summary.
  • Prioritize where the market is in the cycle over point forecasts.
  • Infer expectations before using traditional cheap or expensive language.
  • Treat liquidity, policy, and financing conditions as transmission channels into multiples, earnings expectations, and risk appetite.
  • Distinguish a good asset from a good trade right now.
  • Analyze reflexive loops in which price changes alter narrative, financing access, confidence, and fundamentals.
  • Convert every regime view into a practical implication for the investment case.

Required Analysis Sequence

1. Make the regime call

  • Identify whether conditions are risk-on, risk-off, tightening, easing, reflation, disinflation, early-cycle, late-cycle, or structurally transitioning.
  • State confidence level and major uncertainty if the signals are mixed.

2. Locate the cycle and pendulum

  • Judge whether psychology is tilted toward fear, greed, comfort, or defensiveness.
  • Assess whether consensus is overextended or still under-positioned.

3. Infer expectations already priced in

  • Explain what the market appears to be discounting for growth, inflation, rates, margins, or liquidity.
  • Compare implied expectations with plausible reality, not with a stylized fair-value idea alone.

4. Trace macro and liquidity transmission

  • Explain how rates, credit, liquidity, policy, and macro inflections are transmitting into valuation, earnings expectations, and market leadership.
  • Focus on regime shifts and transmission mechanisms rather than static macro description.

5. Evaluate positioning and asymmetry

  • Judge whether crowding, consensus, and internal market strength make upside or downside asymmetric.
  • Separate strong underlying fundamentals from fragile market positioning.

6. Check reflexive loops

  • Identify whether price strength is feeding narrative strength, financing ease, capital access, confidence, and better fundamentals.
  • Identify the reverse loop when price weakness tightens conditions and damages the narrative.

7. Frame the decision

  • Conclude whether the market context strengthens, weakens, delays, or invalidates the investment case.
  • Use the output structure in references/output-contract.md.

Required References

  • Read references/integrated-framework.md for the full analytical framework.
  • Read references/signal-checklist.md for the reusable checklist.
  • Read references/output-contract.md for mandatory output behavior.

Risk and Uncertainty Rules

  • State uncertainty explicitly when regime evidence is mixed or incomplete.
  • Avoid deterministic regime calls when the signal quality is weak.
  • Distinguish short-term market pressure from medium-term structural change.
  • State break conditions that would force a view change.

Anti-Hallucination Rules

  • Do not fabricate positioning data, policy facts, macro data, or market-internals evidence.
  • Tag statements as [actual], [inference], or [assumption].
  • Use [actual] only for verified facts.
  • Use [inference] for reasoned conclusions drawn from facts.
  • Use [assumption] for scenario inputs or conditional cases.
  • If hard evidence is unavailable, say so and lower confidence rather than filling the gap with certainty.

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 Traditional Market Analysis AI skill do?

Analyze traditional market context for an investment case by identifying the current regime, cycle position, market expectations, liquidity and macro transmission, positioning and crowd psychology, risk asymmetry, and reflexive feedback loops between price, narrative, financing, and fundamentals. Use when an agent must decide what the backdrop in equities, rates, credit, macro, and other traditional markets means for the investment case right now, produce an action-oriented market judgment, and distinguish verified facts from inference and assumptions without relying on generic macro commen...

Why use Traditional Market Analysis on TypingMind?

Because you install it once and use it with any model. Traditional Market 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 Traditional Market Analysis in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/monarchjuno/vibe-investing/tree/main/skills/market-analysis/traditional-market-analysis. 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 Traditional Market 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 Traditional Market Analysis?

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

Is the Traditional Market Analysis AI skill free?

Yes. It is published on GitHub by monarchjuno 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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