Agent skill

Fin Yfinance Data

by criptogus in criptogus/agent-evolve-network

Fetch market and fundamental data via the yfinance Python library — quotes, OHLC history, financial statements, holders, dividends, options, and more.

MITAuto-check passedBusiness, Finance & HR

Install Fin Yfinance Data

skills CLI
$ npx skills add criptogus/agent-evolve-network --skill fin-yfinance-data -a claude-code

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

GitHub CLI
$ gh skill install criptogus/agent-evolve-network fin-yfinance-data --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/criptogus/agent-evolve-network.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/fin-yfinance-data .claude/skills/fin-yfinance-data && 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
fin-yfinance-data
GitHub stars
288
Token cost
~806 tokens
SKILL.md length
311 words
Files
1
Skills in repo
107
Repo updated
First seen
Licence
MIT

At a glance

Fetch market and fundamental data via the yfinance Python library — quotes, OHLC history, financial statements, holders, dividends, options, and more.

  • The user asks for yfinance data work
  • SKILL.md covers Instructions, Always, Never and Examples, plus 1 more section
  • Calls npx
  • Tasks that involve Stock and market analysis

What it does

Fin Yfinance Data is an agent skill from criptogus/agent-evolve-network. Fetch market and fundamental data via the yfinance Python library — quotes, OHLC history, financial statements, holders, dividends, options, and more. Use when the user asks for yfinance data work, or mentions fin, yfinance, data.

Its SKILL.md is about 810 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in Business, Finance & HR, covering Stock and market analysis and Financial analysis. It works with yfinance and Python. The licence is MIT.

When your agent uses it

  • The user asks for yfinance data work
  • Tasks that involve Stock and market analysis
  • Tasks that involve Financial analysis

Example prompts

  • “/fin-yfinance-data”

Requirements

  • Python 3
  • Node.js

What it can do on your machine

Read from SKILL.md and the folder at commit d19b920. 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

    Shell commands in SKILL.md call:

    • npx

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

  • Network

    Links to these hosts (documentation or services it may open):

    • superagentskill.com

    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

Fin Yfinance Data loads about 806 tokens when it runs. Until then it costs about 62 tokens; SKILL.md has 311 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~62
When it runs · the whole SKILL.md, loaded when a task matches
~806

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); files beside SKILL.md are not scanned.

SKILL.md

The full file from criptogus/agent-evolve-network at commit d19b920, republished under its MIT licence (© criptogus). 311 words, ~806 tokens.

Download SKILL.mdSave it as .claude/skills/fin-yfinance-data/SKILL.md (or your agent's skills folder).
name
fin-yfinance-data
description
Fetch market and fundamental data via the yfinance Python library — quotes, OHLC history, financial statements, holders, dividends, options, and more. Use when the user asks for yfinance data work, or mentions fin, yfinance, data.
version
0.1.0
license
MIT
homepage
https://superagentskill.com/marketplace/fin-yfinance-data
source
Super Agent Skill (SAK)

yfinance Data

Use this skill when a user wants raw market or fundamental data for a ticker that yfinance can provide: real-time/last quotes, historical OHLC over valid periods/intervals, financial statements, holders, dividends/splits, options chains, and company info. It writes and runs short Python that calls the appropriate yfinance method, then presents the data cleanly.

It is a data-retrieval skill: identify what the user needs, pick the right yfinance method, validate the period/interval, execute, and format the result. Output is research/educational only, not financial advice; it does not recommend trades.

Instructions

You are a data-retrieval assistant using the yfinance Python library. Step 1 - Ensure yfinance is available (install if missing). Step 2 - Identify what the user needs (quote, history, financials, holders, dividends, options, info) and map it to the appropriate yfinance method. Step 3 - Write and execute short Python using the right method. Use valid periods (1d,5d,1mo,3mo,6mo, 1y,2y,5y,10y,ytd,max) and intervals (1m..3mo); intraday intervals only over short periods. Handle missing/empty data gracefully. Step 4 - Present the data cleanly: format prices to 2 decimals, large numbers with separators, use tables for series, and summarize long time series rather than dumping every row. Research/educational only, not financial advice; do not recommend trades.

Always

  • Fetch data through yfinance rather than answering from memory.
  • Use valid period/interval combinations and handle empty results gracefully.
  • State that output is research/educational, not financial advice.

Never

  • Recommend buying or selling based on the data.
  • Dump entire raw time series when a summary or table is clearer.

Examples

Price history

Input:

Get me 1 year of daily prices for AAPL

Expected output:

Runs yfinance history(period="1y", interval="1d") and returns a clean OHLC summary/table with the
latest close formatted to 2 decimals. Research-only, not advice.
Financials

Input:

Show NVDA's latest income statement

Expected output:

Calls the income-statement method, formats large numbers with separators in a table, and notes the
reporting period. Not a recommendation.

Trust & telemetry

This skill is graded on the Super Agent Skill network: format, substance and adversarial (prompt-injection) testing produce a public Trust Score.

Reinstall or update with npx skills update, or pull the live graded version with npx super-agent install fin-yfinance-data.

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

Files

Just SKILL.md in skills/fin-yfinance-data of criptogus/agent-evolve-network.

Open the folder on GitHubat commit d19b920

Compare with similar skills

Fin Yfinance Data 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.

Fin Yfinance Data compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Fin Yfinance Data this skillcriptogus/agent-evolve-network288—~806Automated safety check: PassMIT
Yfinance Datahimself65/finance-skills3.4k—~1.3kAutomated safety check: PassMIT
US Market Data ToolkitGeeksfino/finskills283—~1.2kAutomated safety check: PassApache-2.0
Value Stock Screenerokikusan-public/stock_skills135—~2.4kAutomated safety check: PassNone
AKShare Financial DataHKUDS/Vibe-Trading35k—~777Automated safety check: PassMIT
Fundamental Factor ScreeningHKUDS/Vibe-Trading35k—~1.7kAutomated safety check: PassMIT

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  • Yfinance Data

    himself65/finance-skills

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  • US Market Data Toolkit

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    Free Python scripts that fetch US stock data, SEC filings, insider trades and macro indicators, and run financial score calculators and portfolio analytics.

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    35k GitHub stars~777 tokensUpdated today
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Works with

Questions about Fin Yfinance Data

What does Fin Yfinance Data do?

Fetch market and fundamental data via the yfinance Python library — quotes, OHLC history, financial statements, holders, dividends, options, and more. Fin Yfinance Data is an agent skill from criptogus/agent-evolve-network. Fetch market and fundamental data via the yfinance Python library — quotes, OHLC history, financial statements, holders, dividends, options, and more.

When should I use Fin Yfinance Data?

Fin Yfinance Data fits situations like: the user asks for yfinance data work; tasks that involve Stock and market analysis; tasks that involve Financial analysis.

How do I install Fin Yfinance Data in Claude Code?

Run `npx skills add criptogus/agent-evolve-network --skill fin-yfinance-data -a claude-code`. Or copy the skill folder (skills/fin-yfinance-data in criptogus/agent-evolve-network) into .claude/skills/fin-yfinance-data in your project. Claude Code loads it when a task matches its description.

How do I install Fin Yfinance Data in Codex?

Run `npx skills add criptogus/agent-evolve-network --skill fin-yfinance-data -a codex`. Or copy the skill folder (skills/fin-yfinance-data in criptogus/agent-evolve-network) into .agents/skills/fin-yfinance-data in your project. Codex loads it when a task matches its description.

Can I use Fin Yfinance Data 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 criptogus/agent-evolve-network --skill fin-yfinance-data -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/fin-yfinance-data, .gemini/skills/fin-yfinance-data, .github/skills/fin-yfinance-data and .opencode/skills/fin-yfinance-data in your project.

What does Fin Yfinance Data need to run?

Going by SKILL.md and its folder, Fin Yfinance Data needs the command-line tools its instructions call (npx). Our summary lists: Python 3; Node.js.

Does Fin Yfinance Data access the network?

SKILL.md names 1 domain. As links in the text: superagentskill.com. This is read from the text; nothing was executed.

Is Fin Yfinance Data 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. Review the folder before installing.

What licence does Fin Yfinance Data use?

Fin Yfinance Data is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Fin Yfinance Data use?

About 806 tokens (SKILL.md is roughly 3.2k 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 Fin Yfinance Data?

Skills that share tags, products or a category with Fin Yfinance Data: Yfinance Data (himself65/finance-skills, 3.4k stars), US Market Data Toolkit (Geeksfino/finskills, 283 stars), Value Stock Screener (okikusan-public/stock_skills, 135 stars) and AKShare Financial Data (HKUDS/Vibe-Trading, 35k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Fin Yfinance Data?

criptogus (a GitHub user) maintains it in criptogus/agent-evolve-network, which has 288 GitHub stars. The repository holds 107 skills in this directory. The repository was last updated on September 9, 2026.

Source: criptogus/agent-evolve-network on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.