Claude Trading Skills is a collection of Claude Code workflows for individual investors who want structured market analysis, charting, economic-calendar review, screening, trade planning, journaling, and risk management. It is designed for people using long-term investing, ETFs, dividend stocks, and disciplined swing trading, and the catalogue entries package these workflows as skills, agents, commands, settings, and instructions.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add tradermonty/claude-trading-skills --skill value-dividend-screenergit clone --depth 1 https://github.com/tradermonty/claude-trading-skillsWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/tradermonty/claude-trading-skills/value-dividend-screener)<a href="https://agentmods.dev/skills/tradermonty/claude-trading-skills/value-dividend-screener"><img src="https://agentmods.dev/badge/skills/tradermonty/claude-trading-skills/value-dividend-screener/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/tradermonty/claude-trading-skills/value-dividend-screener"><img src="https://agentmods.dev/badge/skills/tradermonty/claude-trading-skills/value-dividend-screener.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk warn
- NVIDIA SkillSpector pass
What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00102 | $0.04174 |
| Opus 5 | $0.00051 | $0.02087 |
| Sonnet 5 | $0.00020 | $0.00835 |
| Haiku 4.5 | $0.00010 | $0.00417 |
Grade A, and why
value-dividend-screener scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 9d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
Copies of this mod
2 near-identical copies found in the catalogue:
- value-dividend-screener — 100% identical, 0 lines differ
- value-dividend-screener — 98% identical, 4 lines differ
How it starts
The opening of the file, as written. The whole thing — 563 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Value Dividend Screener
Overview
This skill identifies high-quality dividend stocks that combine value characteristics, attractive income generation, and consistent growth using a two-stage screening approach:
- FINVIZ Elite API (Optional but Recommended): Pre-screen stocks with basic criteria (fast, cost-effective)
- Financial Modeling Prep (FMP) API: Detailed fundamental analysis of candidates
Screen US equities based on quantitative criteria including valuation ratios, dividend metrics, financial health, and profitability. Generate comprehensive reports ranking stocks by composite quality scores with detailed fundamental analysis.
Efficiency Advantage: Using FINVIZ pre-screening can reduce FMP API calls by 90%, making this approach ideal for free-tier API users.
When to Use
Invoke this skill when the user requests:
- "Find high-quality dividend stocks"
- "Screen for value dividend opportunities"
- "Show me stocks with strong dividend growth"
- "Find income stocks trading at reasonable valuations"
- "Screen for sustainable high-yield stocks"
- Any request combining dividend yield, valuation metrics, and fundamental analysis
Workflow
Step 1: Verify API Key Availability
For Two-Stage Screening (Recommended):
Check if both API keys are available:
import os
fmp_api_key = os.environ.get('FMP_API_KEY')
finviz_api_key = os.environ.get('FINVIZ_API_KEY')
If not available, ask user to provide API keys or set environment variables:
export FMP_API_KEY=your_fmp_key_here
export FINVIZ_API_KEY=your_finviz_key_here
For FMP-Only Screening:
Check if FMP API key is available:
import os
api_key = os.environ.get('FMP_API_KEY')
If not available, ask user to provide API key or set environment variable:
export FMP_API_KEY=your_key_here
FINVIZ Elite API Key:
- Requires FINVIZ Elite subscription (~$40/month or ~$330/year)
- Provides access to CSV export of pre-screened results
- Highly recommended for reducing FMP API usage
What ships with it
6 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 9d ago First seen · 563 lines · 102 tokens per session scan A 341bcc1e60f6
value-dividend-screener is a skill published in the GitHub repository tradermonty/claude-trading-skills (2,813 stars, last pushed today), licensed MIT. It adds 102 tokens to every session and 4,174 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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