Agent skill · data analytics · tradermonty
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.
Why this skill is useful
Provides a systematic approach to stock screening using the CANSLIM methodology, which includes specific scoring and ranking algorithms not commonly known.
What it needs
Requires beautifulsoup4, lxml, python, requests installed locally. Requires fmp account access. About 11k tokens when loaded. Last updated 2026-08-06. 2,581 stars on the source repository.
What this skill does
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: Current Earnings, Annual Growth, Newness/New Highs, Supply/Demand, Leadership/RS Rank, Institutional Sponsorship, and Market 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): C (Current Earnings): 15% A (Annual Growth): 20% N (Newness): 15% S (Supply/Demand): 15% L (Leadership/RS Rank): 20% — multi-period weighted RS (3m/6m/12m vs configurable benchmark) I (Institutional): 10% M (Market Direction): 5% Weighted RS Formula: Available periods are re-normalized when some are missing. Default benchmark is ^GSPC; override with --rs-benchmark SPY/QQQ/IWM/.... Fallback hierarchy when multi-period data is incomplete: 1. No benchmark → weighted absolute stock performance + 20% penalty. 2. All multi-period windows missing but >=50 bars of price history → fall back to the legacy 365-day full-window absolute return as the scoring input (20% penalty if no benchmark). 3. <50 bars of price history → score=0 with error set. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills tradermonty/canslim-screener