canslim-screener
Screen US stocks using William O'Neil's CANSLIM growth stock methodology. Use when user requests CANSLIM stock screening, growth stock analysis, momentum stock identification, or wants to find stocks with strong earnings and price momentum following O'Neil's investment system.
npx skills add BaggaT236/AI-Trading-Skills --skill canslim-screener --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# CANSLIM Stock Screener - Phase 3 (Full CANSLIM) ## Overview This skill screens US stocks using William O'Neil's proven CANSLIM methodology, a systematic approach for identifying growth stocks with strong fundamentals and price momentum. CANSLIM analyzes 7 key components: **C**urrent Earnings, **A**nnual Growth, **N**ewness/New Highs, **S**upply/Demand, **L**eadership/RS Rank, **I**nstitutional Sponsorship, and **M**arket Direction. **Phase 3** implements all 7 of 7 components (C, A, N, S, L, I, M), representing **100% of the full methodology**. **Two-Stage Approach:** 1. **Stage 1 (FMP API + Finviz)**: Analyze stock universe with all 7 CANSLIM components 2. **Stage 2 (Reporting)**: Rank by composite score and generate actionable reports **Key Features:** - Composite scoring (0-100 scale) with weighted components - **Finviz fallback** for institutional ownership data (automatic when FMP data incomplete) - Progressive filtering to optimize API usage - JSON + Markdown output formats - Interpretation bands: Exceptional+ (90+), Exceptional (80-89), Strong (70-79), Above Average (60-69) - Bear market protection (M component gating) **Phase 3.1 Component Weights (Original O'Neil weights
- Overview
- When to Use This Skill
- Prerequisites
- Output
- Workflow
- Step 1: Verify API Access and Requirements
- Step 2: Determine Stock Universe
- Step 3: Execute CANSLIM Screening Script
- Step 4: Read and Parse Screening Results
- Step 5: Analyze Top Candidates and Provide Recommendations
- Step 6: Generate User-Facing Report
- Resources
- Scripts Directory (scripts/)
- References Directory (references/)
pip install requests beautifulsoup4 lxml Check environment variable echo $FMP_API_KEY If not set, prompt user to provide it python3 skills/canslim-screener/scripts/screen_canslim.py python3 skills/canslim-screener/scripts/screen_canslim.py \ cd skills/canslim-screener/scripts Basic run (40 stocks, top 20 in report) python3 screen_canslim.py --api-key $FMP_API_KEY Custom parameters
What does the canslim-screener skill do?
Screen US stocks using William O'Neil's CANSLIM growth stock methodology. Use when user requests CANSLIM stock screening, growth stock analysis, momentum stock identification, or wants to find stocks with strong earnings and price momentum following O'Neil's investment system.
How do I install it?
Run `npx skills add BaggaT236/AI-Trading-Skills --skill canslim-screener --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From BaggaT236/AI-Trading-Skills, a repository with 118 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.