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BytesAgain β€Ί Skills β€Ί singa- finance
πŸ¦€ ClawHub

singa- finance

by @1shadow1

Fetch professional stock market data from Yahoo Finance (yfinance) and SEC EDGAR. Use when: user asks about stock prices, market data, company financials, ea...

Versionv1.0.0
Downloads1,375
Stars⭐ 1
#finance#legal
TERMINAL
clawhub install finance-data

πŸ“– About This Skill

name: finance-data description: "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." metadata: { "openclaw": { "emoji": "πŸ“Š", "requires": { "bins": ["python3"] } } }

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):

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

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

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

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)

# 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

# All statements (income, balance sheet, cash flow) β€” 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

python3 scripts/yfinance_query.py info AAPL

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

Shareholders

python3 scripts/yfinance_query.py holders AAPL

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

Analyst Recommendations & Price Targets

python3 scripts/yfinance_query.py analysts AAPL

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

Dividend History

python3 scripts/yfinance_query.py dividends AAPL

Options Chain

# 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

python3 scripts/yfinance_query.py earnings AAPL

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

News

python3 scripts/yfinance_query.py news AAPL

Returns recent news headlines with links.

SEC EDGAR Commands

Free public API β€” no API key required. All US public company filings.

Full-Text Search

# 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

# 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.

# 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:

# 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 "" --section 7

Filing Document Index

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

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

Company Metadata

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)

# 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

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:

python3 scripts/yfinance_query.py quote TSLA

Fundamental analysis:

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):

# 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 "" --section 7

3. Read the risk factors

python3 scripts/sec_edgar.py read-filing --url "" --section 1a

Due diligence / SEC filings:

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 β€” may have a 15-minute delay for real-time prices
  • SEC EDGAR is official SEC data β€” 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)

    • βš™οΈ Configuration

    Install the Python dependency (one-time):

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

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

    export SEC_EDGAR_USER_AGENT="YourName your@email.com"

    πŸ“‹ Tips & Best Practices

  • yfinance data is sourced from Yahoo Finance β€” may have a 15-minute delay for real-time prices
  • SEC EDGAR is official SEC data β€” 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)