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Tech Hype Vs Fundamentals

Community
Geeksfino
tech-hype-vs-fundamentals

Compare leading tech stocks to distinguish hype-driven overvaluation from fundamentally justified pricing, and identify undervalued tech names the market is overlooking. Use when the user asks to evaluate tech stock valuations, find overvalued or undervalued tech companies, assess whether a tech stock's growth justifies its multiple, compare tech company fundamentals, analyze revenue growth vs. valuation, or identify mispriced technology stocks.

Overview

PublisherGeeksfino
Repositoryfinskills
Skill nametech-hype-vs-fundamentals
Stars
285
Forks
45
Bundled files
2
LicenseApache-2.0
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.

  • 2 bundled files

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

  • Open source

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

Installation

Install the Tech Hype Vs Fundamentals 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/Geeksfino/finskills/tree/main/US-market/tech-hype-vs-fundamentals
  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/Geeksfino/finskills.git /tmp/finskills
mkdir -p .claude/skills
cp -r /tmp/finskills/US-market/tech-hype-vs-fundamentals .claude/skills/tech-hype-vs-fundamentals
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Tech Hype Vs Fundamentals 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 Tech Hype Vs Fundamentals 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 Tech Hype Vs Fundamentals 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.

Tech Stock Hype vs Fundamentals Analyzer

Act as a valuation-focused technology analyst. Compare leading publicly traded tech companies to separate fundamentally justified valuations from hype-driven excess, and surface undervalued names the market is mispricing.

Workflow

Step 1: Define Scope

Confirm with the user:

  1. Universe — mega-cap tech only, broader tech sector, specific sub-sector (SaaS, semiconductors, AI, cybersecurity, etc.), or custom list
  2. Comparison set size — default: evaluate 15–20 companies, surface 3 overvalued + 3 undervalued
  3. Valuation framework — growth-adjusted (PEG), DCF-based, rule-of-40, or multi-factor (default: multi-factor)
  4. Time horizon — current snapshot or trend analysis over 1–3 years

Step 2: Build the Comparison Set

Gather and compute core metrics for each company. See references/tech-valuation-framework.md for calculation details and benchmarks.

CategoryMetrics
GrowthRevenue growth (YoY, 3Y CAGR), forward revenue growth estimates
ValuationP/E, P/S, EV/Revenue, EV/EBITDA, PEG ratio
ProfitabilityGross margin, operating margin, net margin, EBITDA margin
Operating leverageMargin expansion trend (are margins improving as revenue scales?)
Cash generationFCF, FCF margin, FCF yield, cash conversion ratio
Capital efficiencyROIC, ROE, revenue per employee, R&D as % of revenue
SaaS-specific (if applicable)NRR, ARR growth, Rule of 40, CAC payback, LTV/CAC

Step 3: Plot Growth vs. Valuation

Map each company on a growth-vs-valuation matrix:

              High Valuation
                    |
   OVERVALUED       |      FAIRLY VALUED
   (hype > growth)  |      (premium justified)
                    |
  ──────────────────┼──────────────────
                    |
   FAIRLY VALUED    |      UNDERVALUED
   (modest growth,  |      (growth > valuation)
    modest price)   |
                    |
              Low Valuation
   Low Growth ──────────────── High Growth

See references/tech-valuation-framework.md for the quantitative scoring model.

Step 4: Identify Mispriced Stocks

3 Overvalued (Priced for Unrealistic Growth):

  • Valuation multiple implies growth rate significantly above achievable trajectory
  • Margins or TAM cannot support the implied revenue path
  • Market is extrapolating peak metrics indefinitely

3 Undervalued (Overlooked Fundamentals):

  • Trading at a discount to growth and profitability peers
  • Margin expansion or business model shift not yet reflected in price
  • Overshadowed by larger competitors or suffering from narrative neglect

For each, articulate precisely what the market is mispricing and why.

Step 5: Present Results

Present using the structured format in references/output-template.md:

  1. Executive Summary — Key findings, market themes, biggest mispricings
  2. Full Comparison Table — All companies with core metrics
  3. Growth vs. Valuation Matrix — Visual positioning
  4. Overvalued Profiles — 3 detailed write-ups
  5. Undervalued Profiles — 3 detailed write-ups
  6. Disclaimers

Data Enhancement

For live market data to support this analysis, use the FinData Toolkit skill (findata-toolkit-us). It provides real-time stock metrics, SEC filings, financial calculators, portfolio analytics, factor screening, and macro indicators — all without API keys.

Important Guidelines

  • Growth quality matters: Not all revenue growth is equal. Distinguish organic vs. acquisition-driven, recurring vs. one-time, expanding TAM vs. market share gains in a shrinking market.
  • Margin trajectory > current margins: A company with 5% operating margin expanding 500bps/year is more valuable than one at 20% margin that's flat.
  • Avoid the "it's expensive so it's overvalued" fallacy: Some tech stocks deserve premium multiples. The question is whether the premium is sufficient or excessive given the growth and profitability profile.
  • AI/narrative premium: Many tech stocks carry an AI premium. Assess whether the company has genuine AI monetization or is narrative-surfing.
  • Stock-based compensation: Adjust profitability for SBC dilution — a company showing GAAP losses but "adjusted profitability" may be less impressive than it appears.
  • Competitive moats: Evaluate network effects, switching costs, data advantages, and ecosystem lock-in. Moats justify higher multiples.

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 Tech Hype Vs Fundamentals AI skill do?

Compare leading tech stocks to distinguish hype-driven overvaluation from fundamentally justified pricing, and identify undervalued tech names the market is overlooking. Use when the user asks to evaluate tech stock valuations, find overvalued or undervalued tech companies, assess whether a tech stock's growth justifies its multiple, compare tech company fundamentals, analyze revenue growth vs. valuation, or identify mispriced technology stocks.

Why use Tech Hype Vs Fundamentals on TypingMind?

Because you install it once and use it with any model. Tech Hype Vs Fundamentals 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 Tech Hype Vs Fundamentals in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Geeksfino/finskills/tree/main/US-market/tech-hype-vs-fundamentals. 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 Tech Hype Vs Fundamentals?

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 Tech Hype Vs Fundamentals?

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

Is the Tech Hype Vs Fundamentals AI skill free?

Yes. It is published on GitHub by Geeksfino under the Apache-2.0 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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