finance-data

Fetch professional stock market data from Yahoo Finance (yfinance) and SEC EDGAR. Use when: user asks about stock prices, market data, company financials, earnings, analyst recommendations, SEC filings (10-K, 10-Q, 8-K), insider transactions, options chains, dividend history, company profiles, XBRL financial concepts, or any equity research task. Supports US stocks, Chinese A-shares (e.g. 600519.SS), and international markets.

3,891 stars

Best use case

finance-data is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Fetch professional stock market data from Yahoo Finance (yfinance) and SEC EDGAR. Use when: user asks about stock prices, market data, company financials, earnings, analyst recommendations, SEC filings (10-K, 10-Q, 8-K), insider transactions, options chains, dividend history, company profiles, XBRL financial concepts, or any equity research task. Supports US stocks, Chinese A-shares (e.g. 600519.SS), and international markets.

Teams using finance-data should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/finance-data/SKILL.md --create-dirs "https://raw.githubusercontent.com/openclaw/skills/main/skills/1shadow1/finance-data/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/finance-data/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How finance-data Compares

Feature / Agentfinance-dataStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Fetch professional stock market data from Yahoo Finance (yfinance) and SEC EDGAR. Use when: user asks about stock prices, market data, company financials, earnings, analyst recommendations, SEC filings (10-K, 10-Q, 8-K), insider transactions, options chains, dividend history, company profiles, XBRL financial concepts, or any equity research task. Supports US stocks, Chinese A-shares (e.g. 600519.SS), and international markets.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

Related Guides

SKILL.md Source

# Finance Data Skill

Fetch professional stock and financial data from **Yahoo Finance** (via yfinance) and **SEC EDGAR** (free public API).

## Setup

Install the Python dependency (one-time):

```bash
pip install -r skills/finance-data/scripts/requirements.txt
```

SEC EDGAR requires a User-Agent header identifying the requester. Set the env var (optional — a default is provided):

```bash
export SEC_EDGAR_USER_AGENT="YourName your@email.com"
```

## Ticker Formats

| Market            | Format  | Example                       |
| ----------------- | ------- | ----------------------------- |
| US stocks         | Symbol  | `AAPL`, `MSFT`, `GOOGL`       |
| Shanghai A-shares | Code.SS | `600519.SS` (Moutai)          |
| Shenzhen A-shares | Code.SZ | `000858.SZ` (Wuliangye)       |
| Hong Kong         | Code.HK | `0700.HK` (Tencent)           |
| Tokyo             | Code.T  | `7203.T` (Toyota)             |
| London            | Code.L  | `HSBA.L` (HSBC)               |
| ETFs / Indices    | Symbol  | `SPY`, `QQQ`, `^GSPC`, `^HSI` |

## Yahoo Finance Commands

All commands output JSON to stdout.

### Current Quote

```bash
python3 scripts/yfinance_query.py quote AAPL
```

Returns: price, volume, market cap, P/E, EPS, 52-week range, moving averages, dividend yield, beta, profit margins, etc.

### Historical Prices (OHLCV)

```bash
# Last month, daily
python3 scripts/yfinance_query.py history AAPL

# Last year, weekly
python3 scripts/yfinance_query.py history AAPL --period 1y --interval 1wk

# Last 5 days, 5-minute bars
python3 scripts/yfinance_query.py history AAPL --period 5d --interval 5m
```

Period options: `1d, 5d, 1mo, 3mo, 6mo, 1y, 2y, 5y, 10y, ytd, max`
Interval options: `1m, 2m, 5m, 15m, 30m, 60m, 90m, 1h, 1d, 5d, 1wk, 1mo, 3mo`

### Financial Statements

```bash
# All statements (income, balance sheet, cash flow) — annual
python3 scripts/yfinance_query.py financials AAPL

# Quarterly income statement only
python3 scripts/yfinance_query.py financials AAPL --statement income --quarterly

# Balance sheet only
python3 scripts/yfinance_query.py financials AAPL --statement balance

# Cash flow only
python3 scripts/yfinance_query.py financials AAPL --statement cashflow
```

### Full Company Profile

```bash
python3 scripts/yfinance_query.py info AAPL
```

Returns all available metadata: sector, industry, description, officers, full-year financials, etc.

### Shareholders

```bash
python3 scripts/yfinance_query.py holders AAPL
```

Returns institutional holders, major holders breakdown, and insider transactions.

### Analyst Recommendations & Price Targets

```bash
python3 scripts/yfinance_query.py analysts AAPL
```

Returns recent analyst recommendations (buy/hold/sell) and consensus price targets.

### Dividend History

```bash
python3 scripts/yfinance_query.py dividends AAPL
```

### Options Chain

```bash
# Nearest expiry (default)
python3 scripts/yfinance_query.py options AAPL

# Specific expiry date
python3 scripts/yfinance_query.py options AAPL --expiry 2025-06-20
```

Returns calls and puts with strike, bid, ask, volume, open interest, implied volatility.

### Earnings

```bash
python3 scripts/yfinance_query.py earnings AAPL
```

Returns quarterly and annual earnings (revenue, earnings, surprise).

### News

```bash
python3 scripts/yfinance_query.py news AAPL
```

Returns recent news headlines with links.

## SEC EDGAR Commands

Free public API — no API key required. All US public company filings.

### Full-Text Search

```bash
# Search across all filings
python3 scripts/sec_edgar.py search --query "artificial intelligence" --limit 10

# Filter by form type and date
python3 scripts/sec_edgar.py search --query "revenue growth" --form-type 10-K --date-from 2024-01-01
```

### Company Filings

```bash
# Recent filings by ticker
python3 scripts/sec_edgar.py filings AAPL --limit 20

# Filter by form type
python3 scripts/sec_edgar.py filings AAPL --form-type 10-K
python3 scripts/sec_edgar.py filings AAPL --form-type 10-Q
python3 scripts/sec_edgar.py filings AAPL --form-type 8-K

# By CIK number
python3 scripts/sec_edgar.py filings 320193 --form-type 10-K
```

Common form types: `10-K` (annual), `10-Q` (quarterly), `8-K` (current events), `DEF 14A` (proxy), `S-1` (IPO), `13F-HR` (institutional holdings).

### Read Filing Content

Download and extract readable text from an SEC filing. Use the `url` from the `filings` command output.

```bash
# Read full filing (first 50000 chars by default)
python3 scripts/sec_edgar.py read-filing --url "https://www.sec.gov/Archives/edgar/data/320193/000032019325000079/aapl-20250927.htm"

# Read a specific 10-K section (much more focused)
python3 scripts/sec_edgar.py read-filing --url "URL" --section 7    # MD&A
python3 scripts/sec_edgar.py read-filing --url "URL" --section 1    # Business
python3 scripts/sec_edgar.py read-filing --url "URL" --section 1a   # Risk Factors
python3 scripts/sec_edgar.py read-filing --url "URL" --section 8    # Financial Statements

# Control output length
python3 scripts/sec_edgar.py read-filing --url "URL" --max-chars 100000
```

10-K section numbers: `1` (Business), `1a` (Risk Factors), `2` (Properties), `5` (Market), `7` (MD&A), `7a` (Quantitative Disclosures), `8` (Financial Statements), `9a` (Controls), `10` (Directors), `11` (Executive Compensation), `12` (Security Ownership).

**Recommended workflow for reading annual reports:**

```bash
# Step 1: find the latest 10-K filing
python3 scripts/sec_edgar.py filings AAPL --form-type 10-K --limit 1

# Step 2: read a specific section using the url from step 1
python3 scripts/sec_edgar.py read-filing --url "<url_from_step_1>" --section 7
```

### Filing Document Index

List all documents within a filing package (useful for finding exhibits, XBRL files, etc.):

```bash
python3 scripts/sec_edgar.py filing-index AAPL --accession "0000320193-25-000079"
```

### Company Metadata

```bash
python3 scripts/sec_edgar.py submissions AAPL
```

Returns company name, CIK, SIC code, address, phone, fiscal year end, exchanges, and filing count.

### Structured Financial Data (XBRL)

```bash
# List all available XBRL concepts for a company
python3 scripts/sec_edgar.py company AAPL

# Get time-series for a specific concept
python3 scripts/sec_edgar.py concept AAPL --concept Revenue
python3 scripts/sec_edgar.py concept AAPL --concept NetIncomeLoss
python3 scripts/sec_edgar.py concept AAPL --concept EarningsPerShareBasic
python3 scripts/sec_edgar.py concept AAPL --concept Assets
python3 scripts/sec_edgar.py concept AAPL --concept StockholdersEquity
```

Useful XBRL concepts: `Revenue`, `NetIncomeLoss`, `EarningsPerShareBasic`, `EarningsPerShareDiluted`, `Assets`, `Liabilities`, `StockholdersEquity`, `OperatingIncomeLoss`, `CashAndCashEquivalentsAtCarryingValue`, `LongTermDebt`.

### Insider Transactions

```bash
python3 scripts/sec_edgar.py insider AAPL --limit 20
```

Returns Forms 3, 4, 5 filings (insider buys/sells/grants) with links to SEC documents.

## Common Workflows

**Quick stock check:**

```bash
python3 scripts/yfinance_query.py quote TSLA
```

**Fundamental analysis:**

```bash
python3 scripts/yfinance_query.py financials MSFT --statement income
python3 scripts/yfinance_query.py financials MSFT --statement balance
python3 scripts/sec_edgar.py concept MSFT --concept Revenue
python3 scripts/sec_edgar.py concept MSFT --concept NetIncomeLoss
```

**Read the latest annual report (10-K):**

```bash
# 1. Find the latest 10-K
python3 scripts/sec_edgar.py filings AAPL --form-type 10-K --limit 1
# 2. Read the MD&A section (most important for investors)
python3 scripts/sec_edgar.py read-filing --url "<url>" --section 7
# 3. Read the risk factors
python3 scripts/sec_edgar.py read-filing --url "<url>" --section 1a
```

**Due diligence / SEC filings:**

```bash
python3 scripts/sec_edgar.py filings NVDA --form-type 10-K --limit 5
python3 scripts/sec_edgar.py insider NVDA --limit 20
python3 scripts/sec_edgar.py submissions NVDA
```

**Compare multiple stocks:**

Run quote or financials commands for each ticker and compare the JSON output side by side.

## Notes

- yfinance data is sourced from Yahoo Finance — may have a 15-minute delay for real-time prices
- SEC EDGAR is official SEC data — always accurate but filings may lag by a few days
- SEC rate limit: max 10 requests/second per IP; the scripts respect this by default
- Chinese A-share tickers use `.SS` (Shanghai) or `.SZ` (Shenzhen) suffix in yfinance
- XBRL concepts are case-sensitive (e.g. `Revenue` not `revenue`)

Related Skills

afrexai-personal-finance

3891
from openclaw/skills

Complete personal finance system — budgeting, debt payoff, investing, tax optimization, net worth tracking, and financial independence planning. Use when managing money, building wealth, paying off debt, planning retirement, or optimizing taxes. Zero dependencies.

Personal Finance

Database Engineering Mastery

3891
from openclaw/skills

> Complete database design, optimization, migration, and operations system. From schema design to production monitoring — covers PostgreSQL, MySQL, SQLite, and general SQL patterns.

Coding & Development

Data Room Builder

3891
from openclaw/skills

Build a structured virtual data room checklist and folder hierarchy for fundraising, M&A, or due diligence.

Workflow & Productivity

Data Privacy & Protection Program

3891
from openclaw/skills

You are a **Data Privacy Officer (DPO) agent** — a comprehensive privacy program architect. You help organizations build, operate, and mature privacy programs that comply with global regulations (GDPR, CCPA/CPRA, LGPD, PIPEDA, POPIA, APPI, PDPA) while enabling business growth.

Privacy & Compliance

Data Migration Planner

3891
from openclaw/skills

Plan, execute, and validate data migrations between systems. Covers schema mapping, ETL pipeline design, rollback strategies, and post-migration validation.

Workflow & Productivity

Data Governance Framework

3891
from openclaw/skills

Assess, score, and remediate your organization's data governance posture across 6 domains.

Security

Data Analyst — AfrexAI ⚡📊

3891
from openclaw/skills

**Transform raw data into decisions. Not just charts — answers.**

Data & Research

data-analysis-partner

3891
from openclaw/skills

智能数据分析 Skill,输入 CSV/Excel 文件和分析需求,输出带交互式 ECharts 图表的 HTML 自包含分析报告

Data & Research

Made-in-China Trade Data Analyst

3891
from openclaw/skills

**Short Description**

ercdata

3891
from openclaw/skills

Store, verify, and manage AI data on the Ethereum blockchain (Base network) using the ERCData standard. Use when an agent needs to store data fingerprints on-chain, verify data integrity, create audit trails, manage access control for private data, or interact with the ERCData smart contract. Supports public and private storage, EIP-712 verification, snapshots, and batch operations.

Security

Data Engineering Command Center

3880
from openclaw/skills

Complete methodology for designing, building, operating, and scaling data pipelines and infrastructure. Zero dependencies — pure agent skill.

Data Engineering

pipeworx-econdata

3891
from openclaw/skills

US economic indicators from the Bureau of Labor Statistics — unemployment, CPI, and employment by industry