Fundamentals

Community

staskh

fundamentals

Get fundamental financial data including financials, earnings, and key metrics. Use when user asks about financials, earnings, revenue, profit, balance sheet, income statement, or company fundamentals.

Overview

Publisher	staskh
Repository	`trading_skills`
Skill name	`fundamentals`
Stars	386
Forks	86
Bundled files	2
License	MIT
Links	Skill source Repository

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 staskh on GitHub. Read the source before you install it.

Installation

Install the Fundamentals AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

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.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/staskh/trading_skills/tree/main/.claude/skills/fundamentals
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.

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/staskh/trading_skills.git /tmp/trading_skills
mkdir -p .claude/skills
cp -r /tmp/trading_skills/.claude/skills/fundamentals .claude/skills/fundamentals

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable 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 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 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.

Fundamentals

Fetch fundamental financial data from Yahoo Finance.

Instructions

Note: If uv is not installed or pyproject.toml is not found, replace uv run python with python in all commands below.

bash
uv run python scripts/fundamentals.py SYMBOL [--type TYPE]

Arguments

SYMBOL - Ticker symbol
--type - Data type: all, financials, earnings, info (default: all)

Output

Returns JSON with:

info - Key metrics (market cap, PE, EPS, dividend, etc.)
financials - Recent quarterly/annual income statement data
earnings - Historical and estimated earnings

Present key metrics clearly. Compare actual vs estimated earnings if relevant.

Piotroski F-Score

Calculate Piotroski's F-Score to evaluate a company's financial strength using 9 fundamental criteria.

Instructions

bash
uv run python scripts/piotroski.py SYMBOL

What is Piotroski F-Score?

Piotroski's F-Score is a fundamental analysis tool developed by Joseph Piotroski that evaluates a company's financial strength using 9 criteria. Each criterion scores 1 point if passed, 0 if failed, for a maximum score of 9.

The 9 Criteria

Positive Net Income - Company is profitable
Positive ROA - Assets are generating returns
Positive Operating Cash Flow - Company generates cash from operations
Cash Flow > Net Income - High-quality earnings (cash exceeds accounting profit)
Lower Long-Term Debt - Decreasing leverage (improving financial position)
Higher Current Ratio - Improving liquidity
No New Shares Issued - No dilution (or share buybacks)
Higher Gross Margin - Improving profitability efficiency
Higher Asset Turnover - More efficient use of assets

Score Interpretation

8-9: Excellent - Very strong financial health
6-7: Good - Strong financial health
4-5: Fair - Moderate financial health
0-3: Poor - Weak financial health

Output

Returns JSON with:

score - F-Score (0-9)
max_score - Maximum possible score (9)
criteria - Detailed breakdown of each criterion with pass/fail status and values
interpretation - Text description of financial health level
data_available - Boolean indicating if year-over-year comparison data is available for criteria 5-9

Implementation Details

Criteria 1-4 use quarterly financial data (most recent year)
Criteria 5-9 use annual financial data for year-over-year comparisons
Compares most recent fiscal year vs previous fiscal year

Use Cases

Use Piotroski F-Score when:

Evaluating fundamental financial strength
Screening for value stocks with improving fundamentals
Assessing financial health trends
Comparing financial strength across companies
Identifying companies with strong fundamentals but undervalued prices

Dependencies

pandas
yfinance

Timezone

All timestamps and time-based calculations must use the America/New_York timezone. All JSON output must include generated_at (NY time string) and data_delay fields.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

scripts/fundamentals.py1 KB
scripts/piotroski.py1 KB

Frequently asked questions

What does the Fundamentals AI skill do?

Why use Fundamentals on TypingMind?

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

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/staskh/trading_skills/tree/main/.claude/skills/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 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 Fundamentals?

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

Is the Fundamentals AI skill free?

Yes. It is published on GitHub by staskh 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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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Fundamentals

Instructions

Arguments

Output

Piotroski F-Score

Instructions

What is Piotroski F-Score?

The 9 Criteria

Score Interpretation

Output

Implementation Details

Use Cases

Dependencies

Timezone

Bundled files

Frequently asked questions

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