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Company Analysis

Community
monarchjuno
company-analysis

Automatically analyze a company or company-related finance situation from a short user prompt such as a company name, "analyze [company]," M&A, LBO, IPO, debt, credit, or risk requests. Use when an agent must infer the correct valuation and finance framework without asking follow-up questions, begin from market-implied expectations instead of immediate fair value, run Reverse DCF before Forward DCF for listed companies, perform web-verified data gathering and deal-radar checks, defend against hallucinations with explicit data tags and uncertainty statements, and produce a plain-text output with no markdown and no row-column tables.

Overview

Publishermonarchjuno
Repositoryvibe-investing
Skill namecompany-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 Company 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/fundamental-analysis/company-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/fundamental-analysis/company-analysis .claude/skills/company-analysis
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Company 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 Company 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 Company 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.

Company Analysis

Overview

Use this skill to produce an IB-style investment analysis from minimal user input. Start from what the current price already implies, not from a fair-value claim, and force every valuation conclusion through verified data, explicit assumptions, and expectation decomposition.

Quick Start

  • If the user provides only a company name or a short prompt such as "[Company] analyze," do not ask clarifying questions. Infer the company type and run the most appropriate workflow immediately.
  • For listed companies, always define the Narrative first and run Reverse DCF before Forward DCF.
  • Run web research before using any revenue, profit, debt, market cap, or transaction figure.
  • Read references/analysis-orchestration.md for routing logic and framework selection.
  • Read references/data-integrity-and-deal-radar.md for hallucination defense and mandatory pre-analysis searches.
  • Read references/output-contract.md for the exact output shape and plain-text rules.

Core Workflow

1. Route the request automatically

  • Infer the requested analysis from the prompt without follow-up questions.
  • Use the default listed-company stack when the intent is ambiguous: Narrative, Reverse DCF, Forward DCF, Trading Comps, Sensitivity, and So What.
  • Use the framework-routing rules in references/analysis-orchestration.md.

2. Gather and tag data before modeling

  • Search the web for actual disclosed financial data before using any revenue, earnings, debt, or valuation number.
  • Tag every number as [Actual], [Estimated], or [Assumption].
  • Never label a number as [Actual] unless the underlying source has been verified and cited.
  • State uncertainty explicitly whenever the data is unavailable, stale, private, disputed, or not yet reported.

3. Run Deal Radar before valuation

  • Search for pending M&A, subsidiary or parent transactions, competitor deals, regulatory or antitrust issues, activism or breakup pressure, and major shareholder ownership changes.
  • Distinguish rumor, official announcement, and active regulatory review.
  • Include only web-verified items with cited sources.

4. Start from Narrative and Expectations

  • Define the story the market is pricing into the current stock or enterprise value.
  • Translate that story into growth, margin, and reinvestment expectations.
  • Run Reverse DCF before any Forward DCF for listed companies.
  • Test whether the implied expectations are realistic relative to industry structure and operating history.

5. Run the relevant framework stack

  • Use DCF on an FCFF basis when the business supports a cash-flow view and the data is sufficient.
  • Use Trading Comps to interpret compressed expectations through multiples, not as a standalone verdict.
  • Use SOTP for holding companies, conglomerates, or businesses with clearly separable segments.
  • Use Sensitivity and Scenario Analysis for all major valuation outputs.
  • Use M&A, LBO, IPO, Credit, or Operating Model frameworks when the prompt directly calls for them.

6. Translate valuation into decision language

  • State what the current price requires, not just what your model says.
  • Quantify the growth CAGR, EBIT margin, and reinvestment rate needed to justify the current price when the expectation gap matters.
  • If your implied value and the current market value differ by more than 30 percent, mark it as caution and explain why.

7. Output in the required format

  • Do not use markdown.
  • Do not use row-column tables.
  • Use the required plain-text block order defined in references/output-contract.md.

Mandatory Rules

  • Do not ask clarifying questions before producing the analysis.
  • Do not fabricate data, comps, transactions, or deal rumors.
  • Do not skip Reverse DCF for listed companies.
  • Do not output unsupported certainty when the underlying information is incomplete.
  • Do not present a fair value first and expectations second.

Guardrails

  • If disclosed financial data cannot be found, say so clearly and explain that the user can provide direct inputs for a more accurate model.
  • If you switch into a hypothetical scenario, mark it as a non-actual example scenario.
  • If peer multiples or transaction data cannot be verified, state that Bloomberg, Capital IQ, or equivalent verification is needed.
  • If private-company financials are not disclosed, state the uncertainty instead of backfilling missing numbers as facts.

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 Company Analysis AI skill do?

Automatically analyze a company or company-related finance situation from a short user prompt such as a company name, "analyze [company]," M&A, LBO, IPO, debt, credit, or risk requests. Use when an agent must infer the correct valuation and finance framework without asking follow-up questions, begin from market-implied expectations instead of immediate fair value, run Reverse DCF before Forward DCF for listed companies, perform web-verified data gathering and deal-radar checks, defend against hallucinations with explicit data tags and uncertainty statements, and produce a plain-text output...

Why use Company Analysis on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/monarchjuno/vibe-investing/tree/main/skills/fundamental-analysis/company-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 Company 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 Company Analysis?

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

Is the Company 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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