Value Dividend Screener
Install this when you want your agent to screen dividend stocks via Financial Modeling Prep APIs with a documented key setup and endpoint usage.
Overview
Value Dividend Screener is an agent skill for the Idea phase that screens dividend stocks using Financial Modeling Prep API endpoints and documented rate limits.
Install
npx skills add https://github.com/tradermonty/claude-trading-skills --skill value-dividend-screenerWhat is this skill?
- Financial Modeling Prep API guide focused on dividend stock screening endpoints
- Documents free tier: 250 requests per day at roughly 5 requests per second
- API key setup via environment variable or CLI flag with optional paid tier scale-up
- Covers stock screener filtering by dividend yield, P/E, P/B, and market cap
- Python-oriented screening script invocation pattern
- FMP free tier: 250 API requests per day
- Documented rate limit: approximately 5 requests per second
Adoption & trust: 959 installs on skills.sh; 1.8k GitHub stars; 2/3 security scanners passed (skills.sh audits).
What problem does it solve?
You want dividend candidates filtered by fundamentals but lack a structured FMP setup and screener endpoint reference your agent can execute.
Who is it for?
Solo builders running personal dividend research or prototyping a CLI screener against FMP’s free tier.
Skip if: Production brokerage execution, compliance-heavy advisory workflows, or screening without your own FMP key and rate-limit discipline.
When should I use this skill?
When screening dividend stocks with FMP’s stock screener and related fundamentals endpoints.
What do I get? / Deliverables
You get a configured FMP key, screener calls, and a Python screening path that produces a yield-focused candidate set for further validation.
- Configured FMP API access pattern
- Dividend-focused screener output or script run against FMP endpoints
Recommended Skills
Journey fit
Dividend screening is research before you commit capital or automate a trading stack—canonical shelf is Idea research. Stock screener and fundamentals pulls are competitive and opportunity discovery, not shipping or operating production trade infra.
How it compares
API-backed equity screener skill, not a backtesting or live order-routing integration.
Common Questions / FAQ
Who is value-dividend-screener for?
Indie developers and solo investors building or automating dividend stock research with Financial Modeling Prep data.
When should I use value-dividend-screener?
Use it during Idea research when filtering dividend yields and valuation metrics, and during Validate scope when sizing whether a screening bot fits API quotas.
Is value-dividend-screener safe to install?
Treat FMP API keys as secrets, never commit them to git, and review the Security Audits panel on this Prism page before running scripts in shared environments.
SKILL.md
READMESKILL.md - Value Dividend Screener
# Financial Modeling Prep (FMP) API Guide ## Overview Financial Modeling Prep provides comprehensive financial data APIs for stocks, forex, cryptocurrencies, and more. This guide focuses on endpoints used for dividend stock screening. ## API Key Setup ### Obtaining an API Key 1. Visit https://financialmodelingprep.com/developer/docs 2. Sign up for a free account 3. Navigate to Dashboard → API Keys 4. Copy your API key ### Free Tier Limits - **250 requests per day** - **Rate limit**: ~5 requests per second - **No credit card required** - Sufficient for daily/weekly screening runs ### Paid Tiers (Optional) - **Starter ($14/month)**: 500 requests/day - **Professional ($29/month)**: 1,000 requests/day - **Enterprise ($99/month)**: 10,000 requests/day ## Setting API Key ### Method 1: Environment Variable (Recommended) **Linux/macOS:** ```bash export FMP_API_KEY=your_api_key_here ``` **Windows (Command Prompt):** ```cmd set FMP_API_KEY=your_api_key_here ``` **Windows (PowerShell):** ```powershell $env:FMP_API_KEY="your_api_key_here" ``` **Persistent (add to shell profile):** ```bash # Add to ~/.bashrc or ~/.zshrc echo 'export FMP_API_KEY=your_api_key_here' >> ~/.bashrc source ~/.bashrc ``` ### Method 2: Command-Line Argument ```bash python3 scripts/screen_dividend_stocks.py --api-key your_api_key_here ``` ## Key Endpoints Used ### 1. Stock Screener **Endpoint:** `/v3/stock-screener` **Purpose:** Initial filtering by dividend yield, P/E, P/B, market cap **Parameters:** - `dividendYieldMoreThan`: Minimum dividend yield (e.g., 3.5) - `priceEarningRatioLowerThan`: Maximum P/E ratio (e.g., 20) - `priceToBookRatioLowerThan`: Maximum P/B ratio (e.g., 2) - `marketCapMoreThan`: Minimum market cap (e.g., 2000000000 = $2B) - `exchange`: Exchanges to include (e.g., "NASDAQ,NYSE") - `limit`: Max results (default: 1000) **Example Request:** ``` https://financialmodelingprep.com/api/v3/stock-screener? dividendYieldMoreThan=3.5& priceEarningRatioLowerThan=20& priceToBookRatioLowerThan=2& marketCapMoreThan=2000000000& exchange=NASDAQ,NYSE& limit=1000& apikey=YOUR_API_KEY ``` **Response Format:** ```json [ { "symbol": "T", "companyName": "AT&T Inc.", "marketCap": 150000000000, "sector": "Communication Services", "industry": "Telecom Services", "beta": 0.65, "price": 20.50, "lastAnnualDividend": 1.11, "volume": 35000000, "exchange": "NYSE", "exchangeShortName": "NYSE", "country": "US", "isEtf": false, "isActivelyTrading": true, "dividendYield": 0.0541, "pe": 7.5, "priceToBook": 1.2 } ] ``` ### 2. Income Statement **Endpoint:** `/v3/income-statement/{symbol}` **Purpose:** Revenue, EPS, net income analysis **Parameters:** - `symbol`: Stock ticker (e.g., "AAPL") - `limit`: Number of periods (e.g., 5 for 5 years) - `period`: "annual" or "quarter" **Example Request:** ``` https://financialmodelingprep.com/api/v3/income-statement/AAPL? limit=5& apikey=YOUR_API_KEY ``` **Key Fields Used:** - `revenue`: Total revenue - `eps`: Earnings per share - `netIncome`: Net income - `date`: Fiscal period end date ### 3. Balance Sheet Statement **Endpoint:** `/v3/balance-sheet-statement/{symbol}` **Purpose:** Debt, equity, liquidity analysis **Parameters:** - `symbol`: Stock ticker - `limit`: Number of periods **Key Fields Used:** - `totalDebt`: Total debt (short-term + long-term) - `totalStockholdersEquity`: Shareholders' equity - `totalCurrentAssets`: Current assets - `totalCurrentLiabilities`: Current liabilities ### 4. Cash Flow Statement **Endpoint:** `/v3/cash-flow-statement/{symbol}` **Purpose:** Free cash flow, dividends paid analysis **Parameters:** - `symbol`: Stock ticker - `limit`: Number of periods **Key Fields Used:** - `operatingCashFlow`: Cash from operations - `capitalExpenditure`: Capex (negative value) - `dividendsPaid`: Dividends paid (negative value) - `freeCashFlow`: OCF - Capex ### 5. Key Metrics **Endpoint:** `/v3/key