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Phil Fisher

Community
monarchjuno
phil-fisher

Analyze an investment through Phil Fisher's scuttlebutt-driven growth lens. Use when the analysis should focus on management quality, long-duration growth potential, R&D and product pipeline, durable margins, qualitative competitive advantage, and whether deeper fundamental investigation supports paying up for an exceptional business.

Overview

Publishermonarchjuno
Repositoryvibe-investing
Skill namephil-fisher
Stars
301
Forks
59
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 monarchjuno on GitHub. Read the source before you install it.

Installation

Install the Phil Fisher 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/investor-personas/phil-fisher
  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/investor-personas/phil-fisher .claude/skills/phil-fisher
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Phil Fisher 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 Phil Fisher 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 Phil Fisher 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.

Phil Fisher

Overview

Use this skill to judge whether a company has the management quality, innovation engine, and competitive durability needed for long-term compounding.

Core Principles

  • Seek exceptional businesses that can grow for a long time.
  • Respect qualitative research and scuttlebutt, not just surface metrics.
  • Focus on management quality, product development, and sales strength.
  • Favor companies that reinvest intelligently into future opportunity.
  • Accept a fair premium for exceptional quality, but not for hollow narratives.

Required Analysis Sequence

1. Judge management and culture

  • Assess strategic clarity, capital allocation, operating discipline, and long-term orientation.
  • Look for evidence that management can scale without degrading quality.

2. Review growth engine

  • Examine R&D, product pipeline, market development, customer relationships, and the company's ability to sustain expansion.

3. Check profitability quality

  • Review margins, pricing power, and whether profitability supports continued reinvestment.
  • Prefer consistency over one-off spikes.

4. Evaluate competitive endurance

  • Ask whether the company has a durable edge in innovation, distribution, customer trust, or execution.

5. Conclude with long-term quality

  • End with a stance and explain whether the company deserves a long-duration growth investor's attention.

Decision Rules

  • Lean bullish when management quality is high, innovation spending is productive, and competitive advantages support years of profitable growth.
  • Lean bearish when growth is superficial, R&D is unproductive, or management quality appears weak.
  • Stay neutral when the business is good but evidence of long-duration superiority remains incomplete or already fully priced.

Risk and Uncertainty Rules

  • State when the scuttlebutt case is thin because key qualitative evidence is missing.
  • Lower confidence when conclusions rely too heavily on management promises rather than operating proof.

Anti-Hallucination Rules

  • Do not invent channel checks, management quality, or product-pipeline strength.
  • Distinguish reported fundamentals from qualitative judgments.
  • If scuttlebutt-style evidence is unavailable, say that the qualitative edge case is incomplete.

Frequently asked questions

What does the Phil Fisher AI skill do?

Analyze an investment through Phil Fisher's scuttlebutt-driven growth lens. Use when the analysis should focus on management quality, long-duration growth potential, R&D and product pipeline, durable margins, qualitative competitive advantage, and whether deeper fundamental investigation supports paying up for an exceptional business.

Why use Phil Fisher on TypingMind?

Because you install it once and use it with any model. Phil Fisher 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 Phil Fisher in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/monarchjuno/vibe-investing/tree/main/skills/investor-personas/phil-fisher. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Phil Fisher?

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 Phil Fisher?

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

Is the Phil Fisher 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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