Agent skill

Dividend Growth Pullback Screener

by tradermonty in tradermonty/claude-trading-skills

A skill your agent uses to find high-quality dividend growth stocks (12%+ annual dividend growth, 1.5%+ yield) that are experiencing temporary pullbacks, identified by RSI oversold conditions (RSI…

MITAuto-check passedBusiness, Finance & HR

Install Dividend Growth Pullback Screener

skills CLI
$ npx skills add tradermonty/claude-trading-skills --skill dividend-growth-pullback-screener -a claude-code

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

GitHub CLI
$ gh skill install tradermonty/claude-trading-skills dividend-growth-pullback-screener --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/tradermonty/claude-trading-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/dividend-growth-pullback-screener .claude/skills/dividend-growth-pullback-screener && 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
dividend-growth-pullback-screener
GitHub stars
3k
Used in
2 other repos
Token cost
~3.4k tokens
SKILL.md length
1,469 words
Files
8 (incl. scripts, references)
Skills in repo
74
Repo updated
First seen
Licence
MIT

At a glance

A skill your agent uses to find high-quality dividend growth stocks (12%+ annual dividend growth, 1.5%+ yield) that are experiencing temporary pullbacks, identified by RSI oversold conditions (RSI…

  • Works in 7 steps: Set API Keys → Execute Screening → Review Results → …
  • Find high-quality dividend growth stocks (12%+ annual dividend growth
  • SKILL.md covers Overview, When to Use This Skill, Prerequisites and Screening Workflow, plus 6 more sections
  • Runs Python scripts from its folder; calls python3; needs FMP_API_KEY and FINVIZ_API_KEY

What it does

Dividend Growth Pullback Screener is an agent skill from tradermonty/claude-trading-skills. Use this skill to find high-quality dividend growth stocks (12%+ annual dividend growth, 1.5%+ yield) that are experiencing temporary pullbacks, identified by RSI oversold conditions (RSI ≤40). This skill combines fundamental dividend analysis with technical timing indicators to identify buying opportunities in strong dividend growers during short-term weakness.

Its SKILL.md is about 3.4k tokens, which your agent loads only when the skill is triggered. The skill folder holds 10 other files, including scripts and reference files (for example `references/dividend_growth_compounding.md`, `references/fmp_api_guide.md` and `references/rsi_oversold_strategy.md`).

It sits in Business, Finance & HR. The repository describes itself as: Claude Code skills for equity investors and traders — market analysis, technical charting, economic calendars, screeners, and trading strategy development. The licence is MIT.

When your agent uses it

  • Find high-quality dividend growth stocks (12%+ annual dividend growth
  • 1.5%+ yield) that are experiencing temporary pullbacks
  • Identified by RSI oversold conditions (RSI ≤40)

Example prompts

  • “/dividend-growth-pullback-screener”

Requirements

  • Python 3
  • A credential in FMP_API_KEY
  • A credential in FINVIZ_API_KEY

Workflow steps

7 steps, taken from the step headings in SKILL.md.

  1. Set API Keys
  2. Execute Screening
  3. Review Results
  4. Analyze Qualified Stocks
  5. Fundamental Screening (FMP API)
  6. Technical Screening (RSI Calculation)
  7. Ranking and Output

What it can do on your machine

Read from SKILL.md and the folder at commit c8d58f0. 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 3 files in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python3

    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):

    • elite.finviz.com

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

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • FMP_API_KEY
    • FINVIZ_API_KEY

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

Context cost

Dividend Growth Pullback Screener loads about 3.4k tokens when it runs, and up to ~14k if it reads all its reference files. Until then it costs about 100 tokens; SKILL.md has 1,469 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~100
When it runs · the whole SKILL.md, loaded when a task matches
~3.4k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~14k

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 tradermonty/claude-trading-skills at commit c8d58f0, republished under its MIT licence (© tradermonty). 1,469 words, ~3,430 tokens.

Download SKILL.mdSave it as .claude/skills/dividend-growth-pullback-screener/SKILL.md (or your agent's skills folder). This skill also uses 7 other files; get the full folder from GitHub.
name
dividend-growth-pullback-screener
description
Use this skill to find high-quality dividend growth stocks (12%+ annual dividend growth, 1.5%+ yield) that are experiencing temporary pullbacks, identified by RSI oversold conditions (RSI ≤40). This skill combines fundamental dividend analysis with technical timing indicators to identify buying opportunities in strong dividend growers during short-term weakness.

Dividend Growth Pullback Screener

Overview

This skill screens for dividend growth stocks that exhibit strong fundamental characteristics but are experiencing temporary technical weakness. It targets stocks with exceptional dividend growth rates (12%+ CAGR) that have pulled back to RSI oversold levels (≤40), creating potential entry opportunities for long-term dividend growth investors.

Investment Thesis: High-quality dividend growth stocks (often yielding 1-2.5%) compound wealth through dividend increases rather than high current yield. Buying these stocks during temporary pullbacks (RSI ≤40) can enhance total returns by combining strong fundamental growth with favorable technical entry timing.

When to Use This Skill

Use this skill when:

  • Looking for dividend growth stocks with exceptional compounding potential (12%+ dividend CAGR)
  • Seeking entry opportunities in quality stocks during temporary market weakness
  • Willing to accept lower current yields (1.5-3%) for higher dividend growth
  • Focusing on total return over 5-10 years rather than current income
  • Market conditions show sector rotations or broad pullbacks affecting quality names

Do NOT use when:

  • Seeking high current income (use value-dividend-screener instead)
  • Requiring immediate dividend yields >3%
  • Looking for deep value plays with strict P/E or P/B requirements
  • Short-term trading focus (<6 months)

Prerequisites

  • FMP API key (required): Set FMP_API_KEY environment variable or pass --fmp-api-key. Free tier (250 calls/day) is sufficient for FMP-only mode (≤40 stocks). Sign up.
  • FINVIZ Elite API key (optional, recommended): Set FINVIZ_API_KEY environment variable or pass --finviz-api-key. Reduces execution time from 10–15 min to 2–3 min. Sign up.
  • Python 3.9+ with the requests library installed.

Screening Workflow

Step 1: Set API Keys

For optimal performance, use FINVIZ Elite API for pre-screening + FMP API for detailed analysis:

bash
# Set both API keys as environment variables
export FMP_API_KEY=your_fmp_key_here
export FINVIZ_API_KEY=your_finviz_key_here

Why Two-Stage?

  • FINVIZ: Fast pre-screening with RSI filter (1 API call → ~10-50 candidates)
  • FMP: Detailed fundamental analysis only on pre-screened candidates
  • Result: Analyze more stocks with fewer FMP API calls (stays within free tier limits)
FMP-Only Approach (Original Method)

If you don't have FINVIZ Elite access:

bash
export FMP_API_KEY=your_key_here

Limitation: FMP free tier (250 requests/day) limits analysis to ~40 stocks. Use --max-candidates 40 to stay within limits.

Step 2: Execute Screening

Two-Stage Screening (RECOMMENDED):

bash
python3 skills/dividend-growth-pullback-screener/scripts/screen_dividend_growth_rsi.py --use-finviz

This executes:

  1. FINVIZ pre-screen: Dividend yield 0.5-3%, Dividend growth 10%+, EPS growth 5%+, Sales growth 5%+, RSI <40
  2. FMP detailed analysis: Verify 12%+ dividend CAGR, calculate exact RSI, analyze fundamentals

FMP-Only Screening:

bash
python3 skills/dividend-growth-pullback-screener/scripts/screen_dividend_growth_rsi.py --max-candidates 40

Customization Options:

bash
# Two-stage with custom parameters
python3 skills/dividend-growth-pullback-screener/scripts/screen_dividend_growth_rsi.py \
  --use-finviz --min-yield 2.0 --min-div-growth 15.0 --rsi-max 35

# FMP-only with custom parameters
python3 skills/dividend-growth-pullback-screener/scripts/screen_dividend_growth_rsi.py \
  --min-yield 2.0 --min-div-growth 10.0 --max-candidates 30

# Provide API keys as arguments (instead of environment variables)
python3 skills/dividend-growth-pullback-screener/scripts/screen_dividend_growth_rsi.py \
  --use-finviz --fmp-api-key YOUR_FMP_KEY --finviz-api-key YOUR_FINVIZ_KEY
Step 3: Review Results

The script generates two outputs:

  1. JSON file: dividend_growth_pullback_results_YYYY-MM-DD.json

    • Structured data with all metrics for further analysis
    • Includes dividend growth rates, RSI values, financial health metrics
  2. Markdown report: dividend_growth_pullback_screening_YYYY-MM-DD.md

    • Human-readable analysis with stock profiles
    • Scenario-based probability assessments
    • Entry timing recommendations
Step 4: Analyze Qualified Stocks

For each qualified stock, the report includes:

Dividend Growth Profile:

  • Current yield and annual dividend
  • 3-year dividend CAGR and consistency
  • Payout ratio and sustainability assessment

Technical Timing:

  • Current RSI value (≤40 = oversold)
  • RSI context (extreme oversold <30 vs. early pullback 30-40)
  • Price action relative to recent trend

Quality Metrics:

  • Revenue and EPS growth (confirms business momentum)
  • Financial health (debt levels, liquidity ratios)
  • Profitability (ROE, profit margins)

Investment Recommendation:

  • Entry timing assessment (immediate vs. wait for confirmation)
  • Risk factors specific to the stock
  • Upside scenarios based on dividend growth compounding

Output

The script saves two files to its configured output location. In current packaged versions the CLI may not accept --output-dir; if that flag is unavailable, run the script from the desired working directory or move the generated files after execution. Some builds write to the repository logs/ directory even when invoked from another directory, so verify the printed paths before reading artifacts.

FileDescription
dividend_growth_pullback_results_YYYY-MM-DD.jsonStructured data with all metrics (yield, dividend CAGR, RSI, composite score, etc.)
dividend_growth_pullback_screening_YYYY-MM-DD.mdHuman-readable report with stock profiles, entry timing, and investment recommendations

Report structure (Markdown):

  • Executive summary (number of candidates, market conditions)
  • Ranked stock profiles with dividend growth profile, technical timing, and quality metrics
  • Entry recommendations based on RSI zone (extreme oversold / strong oversold / early pullback)
  • Disclaimers

Screening Criteria Details

Phase 1: Fundamental Screening (FMP API)

Initial Filter:

  • Dividend Yield ≥ 1.5% (calculated from actual dividend payments)
  • Market Cap ≥ $2 billion (liquidity and stability)
  • Exchange: NYSE, NASDAQ (excludes OTC/pink sheets)

Dividend Growth Analysis:

  • 3-Year Dividend CAGR ≥ 12% (doubles dividend in 6 years)
  • Dividend Consistency: No cuts in past 4 years
  • Payout Ratio < 100% (sustainability check)

Financial Health:

  • Positive revenue growth over 3 years
  • Positive EPS growth over 3 years
  • Debt-to-Equity < 2.0 (manageable leverage)
  • Current Ratio > 1.0 (liquidity)
Phase 2: Technical Screening (RSI Calculation)

RSI Calculation:

  • 14-period RSI using daily closing prices
  • Formula: RSI = 100 - (100 / (1 + RS))
    • RS = Average Gain / Average Loss over 14 periods
  • Data source: FMP historical prices (past 30 days)

RSI Filter:

  • RSI ≤ 40 (oversold/pullback condition)
  • RSI interpretation:
    • < 30: Extreme oversold (potential reversal)
    • 30-40: Early pullback (uptrend correction)
    • 40: Not oversold (excluded)

Phase 3: Ranking and Output

Composite Scoring (0-100):

  • Dividend Growth (40%): Reward higher CAGR and consistency
  • Financial Quality (30%): ROE, profit margins, debt levels
  • Technical Setup (20%): Lower RSI = better entry opportunity
  • Valuation (10%): P/E and P/B for context (not exclusionary)

Stocks ranked by composite score. Top scorers combine exceptional dividend growth with attractive technical entry points.

Understanding the Results

Show full SKILL.md (634 more words)Show less
Interpreting RSI Levels

RSI 25-30 (Extreme Oversold):

  • Often indicates panic selling or negative news
  • Higher risk but potentially highest reward
  • Recommended: Wait for RSI to turn up (sign of stabilization)
  • Entry: Scale in with 50% position, add on RSI >30

RSI 30-35 (Strong Oversold):

  • Normal correction in strong uptrend
  • Lower risk than extreme oversold
  • Recommended: Can initiate position immediately
  • Entry: Full position acceptable, set stop loss 5-8% below

RSI 35-40 (Early Pullback):

  • Mild weakness in uptrend
  • Lowest risk of further decline
  • Recommended: Conservative entry for high conviction stocks
  • Entry: Full position, tight stop loss 3-5% below
Dividend Growth Compounding Examples

12% Dividend CAGR (Minimum Threshold):

  • Starting Yield: 1.5%
  • Year 6: 2.96% yield on cost (doubled)
  • Year 12: 5.85% yield on cost (4x)
  • Example: Visa (V), Mastercard (MA) historical profile

15% Dividend CAGR (Excellent):

  • Starting Yield: 1.8%
  • Year 6: 4.08% yield on cost (2.3x)
  • Year 12: 9.22% yield on cost (5.1x)
  • Example: Microsoft (MSFT) 2010-2020 period

20% Dividend CAGR (Exceptional):

  • Starting Yield: 2.0%
  • Year 6: 6.00% yield on cost (3x)
  • Year 12: 18.0% yield on cost (9x)
  • Example: Apple (AAPL) 2012-2020 period

Key Insight: Lower starting yield + high growth > high starting yield + low growth over 10+ years.

Troubleshooting

No Results Found

Possible Causes:

  1. Market conditions: Strong bull market with few oversold stocks
  2. Criteria too strict: 12% dividend growth is rare (5-10 stocks typically qualify)
  3. RSI threshold too low: Consider raising to RSI ≤45 for more candidates

Solutions:

  • Relax RSI threshold: --rsi-max 45 (early pullback phase)
  • Lower dividend growth: --min-div-growth 10.0 (still excellent growth)
  • Lower minimum yield: --min-yield 1.0 (capture more growth stocks)
API Rate Limit Reached

FMP Free Tier Limits:

  • 250 requests/day
  • Each stock analyzed requires 6 API calls (quote, dividend, prices, income, balance, cashflow, metrics)
  • Maximum ~40 stocks per day in FMP-only mode

Solutions:

1. Use FINVIZ Two-Stage Approach (RECOMMENDED)

bash
python3 skills/dividend-growth-pullback-screener/scripts/screen_dividend_growth_rsi.py --use-finviz
  • FINVIZ pre-screening: 1 API call → 10-50 candidates (already filtered by RSI)
  • FMP analysis: 6 calls × 10-50 stocks = 60-300 FMP calls
  • Advantage: FINVIZ RSI filter dramatically reduces candidates, staying within FMP limits

2. Limit FMP-Only Candidates

bash
python3 skills/dividend-growth-pullback-screener/scripts/screen_dividend_growth_rsi.py --max-candidates 40

3. Wait 24 Hours for Rate Limit Reset

  • FMP resets at UTC midnight

4. Upgrade to FMP Paid Plan

  • Starter ($14/month): 500 requests/day
  • Professional ($29/month): 1,000 requests/day

Note: FINVIZ Elite subscription ($40/month) + FMP free tier is more cost-effective than FMP paid plans for this use case.

RSI Calculation Errors

Issue: "Insufficient price data for RSI calculation"

Cause: Stock has less than 30 days of trading history (IPO or inactive)

Solution: Script automatically skips stocks with insufficient data. No action needed.

Combining with Other Skills

Pre-Screening Context:

  1. Market News Analyst → Identify sector rotations or market pullbacks
  2. Breadth Chart Analyst → Confirm broader market oversold conditions
  3. Economic Calendar Fetcher → Check for upcoming rate decisions or macro events

Post-Screening Analysis:

  1. Technical Analyst → Analyze individual stock charts for qualified candidates
  2. US Stock Analysis → Deep dive on specific stocks before entry
  3. Backtest Expert → Validate RSI + dividend growth strategy historically

Example Workflow:

1. Market News Analyst: "Market pulled back 5% this week on Fed hawkish comments"
2. Breadth Chart Analyst: Confirms market oversold (S&P breadth weak)
3. Dividend Growth Pullback Screener: Finds 8 quality dividend growers with RSI <35
4. Technical Analyst: Analyze top 3 candidates for support levels and entry timing
5. Execute: Enter scaled positions with 6-12 month time horizon

Resources

scripts/

screen_dividend_growth_rsi.py - Main screening script

  • Integrates FMP API for fundamental data
  • Calculates 14-period RSI from historical prices
  • Applies multi-phase filtering and ranking
  • Outputs JSON and markdown reports
references/

rsi_oversold_strategy.md - RSI indicator explanation

  • How RSI identifies oversold conditions
  • Difference between extreme oversold (<30) vs. early pullback (30-40)
  • Combining RSI with fundamental analysis
  • False positive management and risk mitigation

dividend_growth_compounding.md - Dividend growth mathematics

  • Power of 12%+ dividend CAGR over time
  • Yield vs. growth trade-offs
  • Historical examples (MSFT, V, MA, AAPL)
  • Quality characteristics of dividend growth stocks

fmp_api_guide.md - API usage documentation

  • API key setup and management
  • Endpoint documentation for screening
  • Rate limiting strategies
  • Error handling and troubleshooting

Disclaimer: This screening tool is for informational purposes only. Past dividend growth does not guarantee future performance. Conduct thorough due diligence before making investment decisions. RSI oversold conditions do not guarantee price reversals - stocks can remain oversold for extended periods.

© tradermonty, 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 7 other files (scripts, references) in skills/dividend-growth-pullback-screener of tradermonty/claude-trading-skills.

  • SKILL.md
  • references/dividend_growth_compounding.md
  • references/fmp_api_guide.md
  • references/rsi_oversold_strategy.md
  • requirements.txt
  • scripts/screen_dividend_growth_rsi.py
  • scripts/tests/test_fmp_stable.py
  • scripts/tests/test_screen_dividend_growth_rsi.py

Open the folder on GitHubat commit c8d58f0

Used in 2 other repositories

We found 2 copies of this SKILL.md (exact, near-identical or edited) in other folders, from 2 other GitHub owners. This page covers the copy in tradermonty/claude-trading-skills, which our catalogue first saw on October 7, 2026.

Compare with similar skills

Dividend Growth Pullback Screener 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.

Dividend Growth Pullback Screener compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Dividend Growth Pullback Screener this skilltradermonty/claude-trading-skills3k2 repos~3.4kAutomated safety check: PassMIT
Creating Financial ModelsChen-zexi/open-ptc-agent7293 repos~1.3kAutomated safety check: PassMIT
Stock APIzhangxiangliang/stock-api2k—~507Automated safety check: PassMIT
Itr Walakaranb192/itr-wala871—~3.6kAutomated safety check: PassMIT
Tushare Datazillionare/zillionare3222 repos~2.3kAutomated safety check: PassNone
Cc Sdd New Agentgotalab/cc-sdd3.7k—~1.1kAutomated safety check: PassMIT

Similar skills

  • Creating Financial Models

    Chen-zexi/open-ptc-agent

    This skill provides an advanced financial modeling suite with DCF analysis, sensitivity testing, Monte Carlo simulations, and scenario planning for investment decisions

    729 GitHub starsUsed in 3 repos~1.3k tokens
    Business, Finance & HRAuto-check passed
  • Stock API

    zhangxiangliang/stock-api

    Fetch real-time stock quotes, K-line (candlestick) history, and search symbols for China A-shares, Hong Kong, and US markets.

    2k GitHub stars~507 tokensUpdated yesterday
    Business, Finance & HRAuto-check passed
  • Itr Wala

    karanb192/itr-wala

    File Indian income tax returns (ITR) for FY 2025-26 / AY 2026-27.

    871 GitHub stars~3.6k tokensUpdated 7 days ago
    Business, Finance & HRAuto-check passed
  • Tushare Data

    zillionare/zillionare

    面向中文自然语言的 Tushare 数据研究技能。用于把“看看这只股票最近怎么样”“帮我查财报趋势”“最近哪个板块最强”“北向资金在买什么”“给我导出一份行情数据”这类请求,转成可执行的数据获取、清洗、对比、筛选、导出与简要分析流程。适用于 A 股、指数、ETF/基金、财务、估值、资金流、公告新闻、板块概念与宏观数据等研究场景。

    322 GitHub starsUsed in 2 repos~2.3k tokens
    Business, Finance & HRAuto-check passed
  • Cc Sdd New Agent

    gotalab/cc-sdd

    Add or extend coding-agent support in cc-sdd by executing the SOP in docs/cc-sdd/sop-new-agent.md end-to-end.

    3.7k GitHub stars~1.1k tokensUpdated 18 days ago
    Business, Finance & HRAuto-check passed
  • DBS Business Toolkit Entry

    dontbesilent2025/dbskill

    Chinese-language entry skill for the dontbesilent business toolkit: onboards new users, orchestrates tasks across sub-skills, runs numbered prompts and lists hidden ones.

    11k GitHub stars~2k tokensUpdated yesterday
    Business, Finance & HRAuto-check passed

More from tradermonty/claude-trading-skills

All 74 skills in this repo
  • Technical Analyst

    tradermonty/claude-trading-skills

    This skill should be used when analyzing weekly price charts for stocks, stock indices, cryptocurrencies, or forex pairs.

    3k GitHub starsUsed in 4 repos~4.6k tokens
    Auto-check passed
  • Theme Detector

    tradermonty/claude-trading-skills

    Detect and analyze trending market themes across sectors. An agent skill from tradermonty/claude-trading-skills.

    3k GitHub starsUsed in 2 repos~4.9k tokens
    Auto-check passed
  • Trader Memory Core

    tradermonty/claude-trading-skills

    Track investment theses across their lifecycle — from screening idea to closed position with postmortem.

    3k GitHub starsUsed in 2 repos~4.3k tokens
    Auto-check passed
  • Edge Strategy Reviewer

    tradermonty/claude-trading-skills

    Critically review strategy drafts from edge-strategy-designer for edge plausibility, overfitting risk, sample size adequacy, and execution realism.

    3k GitHub starsUsed in 1 repo~988 tokens
    Auto-check passed
  • Sector Analyst

    tradermonty/claude-trading-skills

    This skill should be used when analyzing sector rotation patterns and market cycle positioning.

    3k GitHub starsUsed in 1 repo~2.3k tokens
    Auto-check passed
  • Stanley Druckenmiller Investment

    tradermonty/claude-trading-skills

    Druckenmiller Strategy Synthesizer - Integrates 8 upstream skill outputs (Market Breadth, Uptrend Analysis, Market Top, Macro Regime, FTD Detector, VCP Screener, Theme Detector, CANSLIM Screener)…

    3k GitHub starsUsed in 1 repo~2k tokens
    Auto-check passed

Questions about Dividend Growth Pullback Screener

What does Dividend Growth Pullback Screener do?

A skill your agent uses to find high-quality dividend growth stocks (12%+ annual dividend growth, 1.5%+ yield) that are experiencing temporary pullbacks, identified by RSI oversold conditions (RSI…. Dividend Growth Pullback Screener is an agent skill from tradermonty/claude-trading-skills.5%+ yield) that are experiencing temporary pullbacks, identified by RSI oversold conditions (RSI ≤40).

When should I use Dividend Growth Pullback Screener?

Dividend Growth Pullback Screener fits situations like: find high-quality dividend growth stocks (12%+ annual dividend growth; 1.5%+ yield) that are experiencing temporary pullbacks; identified by RSI oversold conditions (RSI ≤40).

How do I install Dividend Growth Pullback Screener in Claude Code?

Run `npx skills add tradermonty/claude-trading-skills --skill dividend-growth-pullback-screener -a claude-code`. Or copy the skill folder (skills/dividend-growth-pullback-screener in tradermonty/claude-trading-skills) into .claude/skills/dividend-growth-pullback-screener in your project. Claude Code loads it when a task matches its description.

How do I install Dividend Growth Pullback Screener in Codex?

Run `npx skills add tradermonty/claude-trading-skills --skill dividend-growth-pullback-screener -a codex`. Or copy the skill folder (skills/dividend-growth-pullback-screener in tradermonty/claude-trading-skills) into .agents/skills/dividend-growth-pullback-screener in your project. Codex loads it when a task matches its description.

Can I use Dividend Growth Pullback Screener 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 tradermonty/claude-trading-skills --skill dividend-growth-pullback-screener -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/dividend-growth-pullback-screener, .gemini/skills/dividend-growth-pullback-screener, .github/skills/dividend-growth-pullback-screener and .opencode/skills/dividend-growth-pullback-screener in your project.

What does Dividend Growth Pullback Screener need to run?

Going by SKILL.md and its folder, Dividend Growth Pullback Screener needs Python for the scripts in its folder, the command-line tools its instructions call (python3) and credentials named FMP_API_KEY and FINVIZ_API_KEY. Our summary lists: Python 3; A credential in FMP_API_KEY; A credential in FINVIZ_API_KEY.

Does Dividend Growth Pullback Screener access the network?

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

Is Dividend Growth Pullback Screener 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 Dividend Growth Pullback Screener use?

Dividend Growth Pullback Screener 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 Dividend Growth Pullback Screener use?

About 3.4k tokens (SKILL.md is roughly 14k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 11k tokens, read only when the agent opens those files.

What are the alternatives to Dividend Growth Pullback Screener?

Skills that share tags, products or a category with Dividend Growth Pullback Screener: Creating Financial Models (Chen-zexi/open-ptc-agent, 729 stars), Stock API (zhangxiangliang/stock-api, 2k stars), Itr Wala (karanb192/itr-wala, 871 stars) and Tushare Data (zillionare/zillionare, 322 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Dividend Growth Pullback Screener?

tradermonty (a GitHub user) maintains it in tradermonty/claude-trading-skills, which has 2,982 GitHub stars. The repository holds 74 skills in this directory. The repository was last updated on October 11, 2026.

Source: tradermonty/claude-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.