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Agent skill

Fundamentals

by staskh in staskh/trading_skills

Get fundamental financial data including financials, earnings, and key metrics.

MITAuto-check passedBusiness, Finance & HR

Install Fundamentals

skills CLI
$ npx skills add staskh/trading_skills --skill fundamentals -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install staskh/trading_skills fundamentals --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/staskh/trading_skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.claude/skills/fundamentals .claude/skills/fundamentals && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
fundamentals
GitHub stars
374
Token cost
~836 tokens
SKILL.md length
367 words
Files
3 (incl. scripts)
Skills in repo
28
Repo updated
First seen
Licence
MIT

At a glance

Get fundamental financial data including financials, earnings, and key metrics.

  • Works in 9 steps: Positive Net Income - Company is… → Positive ROA - Assets are generating… → Positive Operating Cash Flow - Company… → …
  • User asks about financials
  • SKILL.md covers Instructions, Arguments, Output and Piotroski F-Score, plus 2 more sections
  • Runs Python scripts from its folder; calls uv

What it does

Fundamentals is an agent skill from staskh/trading_skills. 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.

Its SKILL.md is about 840 tokens, which your agent loads only when the skill is triggered. The skill folder holds 3 other files, including scripts (for example `scripts/fundamentals.py` and `scripts/piotroski.py`).

It sits in Business, Finance & HR, covering Financial analysis. The repository describes itself as: Claude powered advisor system for option traders. The licence is MIT.

When your agent uses it

  • User asks about financials
  • Income statement
  • Company fundamentals

Example prompts

  • “/fundamentals”

Requirements

  • Python 3

Workflow steps

9 steps, taken from the first numbered list in SKILL.md.

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

What it can do on your machine

Read from SKILL.md and the folder at commit b71a74f. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 2 files in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • uv

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use uv, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Fundamentals loads about 836 tokens when it runs. Until then it costs about 54 tokens; SKILL.md has 367 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~54
When it runs · the whole SKILL.md, loaded when a task matches
~836

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from staskh/trading_skills at commit b71a74f, republished under its MIT licence (© staskh). 367 words, ~836 tokens.

Download SKILL.mdSave it as .claude/skills/fundamentals/SKILL.md (or your agent's skills folder). This skill also uses 2 other files; get the full folder from GitHub.
name
fundamentals
description
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.
dependencies
trading-skills

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
  1. Positive Net Income - Company is profitable
  2. Positive ROA - Assets are generating returns
  3. Positive Operating Cash Flow - Company generates cash from operations
  4. Cash Flow > Net Income - High-quality earnings (cash exceeds accounting profit)
  5. Lower Long-Term Debt - Decreasing leverage (improving financial position)
  6. Higher Current Ratio - Improving liquidity
  7. No New Shares Issued - No dilution (or share buybacks)
  8. Higher Gross Margin - Improving profitability efficiency
  9. Higher Asset Turnover - More efficient use of assets
Show full SKILL.md (154 more words)Show less
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.

© staskh, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 2 other files (scripts) in .claude/skills/fundamentals of staskh/trading_skills.

  • SKILL.md
  • scripts/fundamentals.py
  • scripts/piotroski.py

Open the folder on GitHubat commit b71a74f

Compare with similar skills

Fundamentals next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Fundamentals compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Fundamentals this skillstaskh/trading_skills374—~836Automated safety check: PassMIT
Financial Analyzinghuangjia2019/claude-code-engineering1.1k1 repos~474Automated safety check: PassNone
Longbridge Earningshelsome/folio2691 repos~2.5kAutomated safety check: PassNone
Earnings AnalysisWind-Alice/AliceMarket1283 repos~2.2kAutomated safety check: PassNone
Buy Side Equity Research Memohaskaomni/serenity-skill632—~3.8kAutomated safety check: PassMIT
ERPClaw ERP Controlleravansaber/erpclaw114—~15kAutomated safety check: PassGPL-3.0

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Categories

Questions about Fundamentals

What does Fundamentals do?

Get fundamental financial data including financials, earnings, and key metrics. Fundamentals is an agent skill from staskh/trading_skills. Get fundamental financial data including financials, earnings, and key metrics.

When should I use Fundamentals?

Fundamentals fits situations like: user asks about financials; income statement; company fundamentals.

How do I install Fundamentals in Claude Code?

Run `npx skills add staskh/trading_skills --skill fundamentals -a claude-code`. Or copy the skill folder (.claude/skills/fundamentals in staskh/trading_skills) into .claude/skills/fundamentals in your project. Claude Code loads it when a task matches its description.

How do I install Fundamentals in Codex?

Run `npx skills add staskh/trading_skills --skill fundamentals -a codex`. Or copy the skill folder (.claude/skills/fundamentals in staskh/trading_skills) into .agents/skills/fundamentals in your project. Codex loads it when a task matches its description.

Can I use Fundamentals in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add staskh/trading_skills --skill fundamentals -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/fundamentals, .gemini/skills/fundamentals, .github/skills/fundamentals and .opencode/skills/fundamentals in your project.

What does Fundamentals need to run?

Going by SKILL.md and its folder, Fundamentals needs Python for the scripts in its folder and the command-line tools its instructions call (uv). Our summary lists: Python 3.

Does Fundamentals access the network?

SKILL.md contains no URLs. Its commands use uv, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Fundamentals safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Fundamentals use?

Fundamentals is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Fundamentals use?

About 836 tokens (SKILL.md is roughly 3.3k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Fundamentals?

Skills that share tags, products or a category with Fundamentals: Financial Analyzing (huangjia2019/claude-code-engineering, 1.1k stars), Longbridge Earnings (helsome/folio, 269 stars), Earnings Analysis (Wind-Alice/AliceMarket, 128 stars) and Buy Side Equity Research Memo (haskaomni/serenity-skill, 632 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Fundamentals?

staskh (a GitHub user) maintains it in staskh/trading_skills, which has 374 GitHub stars. The repository holds 28 skills in this directory. The repository was last updated on September 28, 2026.

Source: staskh/trading_skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.