canslim-screener

Name: canslim-screener
Author: mphinance

15stars3forks

How to install canslim-screener?

mphinance/alpha-skills/canslim-screener

$npx -y skills add mphinance/alpha-skills --skill canslim-screener

Installs into the current project.

Summary

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.

Files · 1

View on GitHub

SKILL.md

1	# CANSLIM Stock Screener - Phase 3 (Full CANSLIM)
2
3	## Overview
4
5	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.
6
7	Phase 3 implements all 7 of 7 components (C, A, N, S, L, I, M), representing 100% of the full methodology.
8
9	Two-Stage Approach:
10	1. Stage 1 (FMP API + Finviz): Analyze stock universe with all 7 CANSLIM components
11	2. Stage 2 (Reporting): Rank by composite score and generate actionable reports
12
13	Key Features:
14	- Composite scoring (0-100 scale) with weighted components
15	- Finviz fallback for institutional ownership data (automatic when FMP data incomplete)
16	- Progressive filtering to optimize API usage
17	- JSON + Markdown output formats
18	- Interpretation bands: Exceptional+ (90+), Exceptional (80-89), Strong (70-79), Above Average (60-69)
19	- Bear market protection (M component gating)
20
21	Phase 3 Component Weights (Original O'Neil weights):
22	- C (Current Earnings): 15%
23	- A (Annual Growth): 20%
24	- N (Newness): 15%
25	- S (Supply/Demand): 15%
26	- L (Leadership/RS Rank): 20%
27	- I (Institutional): 10%
28	- M (Market Direction): 5%
29
30	Future Phases:
31	- Phase 4: FINVIZ Elite integration → 10x faster execution
32
33	---
34
35	## When to Use This Skill
36
37	Explicit Triggers:
38	- "Find CANSLIM stocks"
39	- "Screen for growth stocks using O'Neil's method"
40	- "Which stocks have strong earnings and momentum?"
41	- "Identify stocks near 52-week highs with accelerating earnings"
42	- "Run a CANSLIM screener on [sector/universe]"
43
44	Implicit Triggers:
45	- User wants to identify multi-bagger candidates
46	- User is looking for growth stocks with proven fundamentals
47	- User wants systematic stock selection based on historical winners
48	- User needs a ranked list of stocks meeting O'Neil's criteria
49
50	When NOT to Use:
51	- Value investing focus (use value-dividend-screener instead)
52	- Income/dividend focus (use dividend-growth-pullback-screener instead)
53	- Bear market conditions (M component will flag - consider raising cash)
54
55	---
56
57	## Prerequisites
58
59	API Requirements:
60	- FMP API key (free tier: 250 calls/day, sufficient for 35 stocks; Starter tier $29.99/mo for 40+ stocks)
61	- Sign up: https://site.financialmodelingprep.com/developer/docs
62	- Set via environment variable: `export FMP_API_KEY=your_key_here`
63
64	Python Dependencies:
65	- Python 3.7+
66	- `requests` (FMP API calls)
67	- `beautifulsoup4` (Finviz web scraping)
68	- `lxml` (HTML parsing)
69
70	Installation:
71	```bash
72	pip install requests beautifulsoup4 lxml
73	```
74
75	---
76
77	## Output
78
79	Output Directory: `reports/` (default) or custom via `--output-dir`
80
81	Generated Files:
82	- `canslim_screener_YYYY-MM-DD_HHMMSS.json` - Structured data for programmatic use
83	- `canslim_screener_YYYY-MM-DD_HHMMSS.md` - Human-readable report
84
85	Report Contents:
86	- Market Condition Summary (trend, M score, warnings)
87	- Top N CANSLIM Candidates (ranked by composite score)
88	- Component Breakdown for each stock (C, A, N, S, L, I, M scores with details)
89	- Rating interpretation (Exceptional+/Exceptional/Strong/Above Average)
90	- Quality warnings and data source notes
91	- Summary statistics (rating distribution)
92
93	Rating Bands:
94	- Exceptional+ (90-100): All components near-perfect, aggressive buy
95	- Exceptional (80-89): Outstanding fundamentals + momentum, strong buy
96	- Strong (70-79): Solid across components, standard buy
97	- Above Average (60-69): Meets thresholds with minor weaknesses, buy on pullback
98
99	---
100
101	## Workflow
102
103	### Step 1: Verify API Access and Requirements
104
105	Check if user has FMP API key configured:
106
107	```bash
108	# Check environment variable
109	echo $FMP_API_KEY
110
111	# If not set, prompt user to provide it
112	```
113
114	Requirements:
115	- FMP API key (free tier: 250 calls/day, sufficient for 40 stocks)
116	- Python 3.7+ with required libraries:
117	- `requests` (FMP API calls)
118	- `beautifulsoup4` (Finviz web scraping)
119	- `lxml` (HTML parsing)
120
121	Installation:
122	```bash
123	pip install requests beautifulsoup4 lxml
124	```
125
126	If API key is missing, guide user to:
127	1. Sign up at https://site.financialmodelingprep.com/developer/docs
128	2. Get free API key (250 calls/day)
129	3. Set environment variable: `export FMP_API_KEY=your_key_here`
130
131	### Step 2: Determine Stock Universe
132
133	Option A: Default Universe (Recommended)
134	Use top 40 S&P 500 stocks by market cap (predefined in script):
135
136	```bash
137	python3 skills/canslim-screener/scripts/screen_canslim.py
138	```
139
140	Option B: Custom Universe
141	User provid

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canslim-screener

15stars3forks

View on GitHub

How to install canslim-screener?

mphinance/alpha-skills/canslim-screener

$npx -y skills add mphinance/alpha-skills --skill canslim-screener

Installs into the current project.

Summary

Files · 1

View on GitHub

SKILL.md

1	# CANSLIM Stock Screener - Phase 3 (Full CANSLIM)
2
3	## Overview
4
5	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.
6
7	Phase 3 implements all 7 of 7 components (C, A, N, S, L, I, M), representing 100% of the full methodology.
8
9	Two-Stage Approach:
10	1. Stage 1 (FMP API + Finviz): Analyze stock universe with all 7 CANSLIM components
11	2. Stage 2 (Reporting): Rank by composite score and generate actionable reports
12
13	Key Features:
14	- Composite scoring (0-100 scale) with weighted components
15	- Finviz fallback for institutional ownership data (automatic when FMP data incomplete)
16	- Progressive filtering to optimize API usage
17	- JSON + Markdown output formats
18	- Interpretation bands: Exceptional+ (90+), Exceptional (80-89), Strong (70-79), Above Average (60-69)
19	- Bear market protection (M component gating)
20
21	Phase 3 Component Weights (Original O'Neil weights):
22	- C (Current Earnings): 15%
23	- A (Annual Growth): 20%
24	- N (Newness): 15%
25	- S (Supply/Demand): 15%
26	- L (Leadership/RS Rank): 20%
27	- I (Institutional): 10%
28	- M (Market Direction): 5%
29
30	Future Phases:
31	- Phase 4: FINVIZ Elite integration → 10x faster execution
32
33	---
34
35	## When to Use This Skill
36
37	Explicit Triggers:
38	- "Find CANSLIM stocks"
39	- "Screen for growth stocks using O'Neil's method"
40	- "Which stocks have strong earnings and momentum?"
41	- "Identify stocks near 52-week highs with accelerating earnings"
42	- "Run a CANSLIM screener on [sector/universe]"
43
44	Implicit Triggers:
45	- User wants to identify multi-bagger candidates
46	- User is looking for growth stocks with proven fundamentals
47	- User wants systematic stock selection based on historical winners
48	- User needs a ranked list of stocks meeting O'Neil's criteria
49
50	When NOT to Use:
51	- Value investing focus (use value-dividend-screener instead)
52	- Income/dividend focus (use dividend-growth-pullback-screener instead)
53	- Bear market conditions (M component will flag - consider raising cash)
54
55	---
56
57	## Prerequisites
58
59	API Requirements:
60	- FMP API key (free tier: 250 calls/day, sufficient for 35 stocks; Starter tier $29.99/mo for 40+ stocks)
61	- Sign up: https://site.financialmodelingprep.com/developer/docs
62	- Set via environment variable: `export FMP_API_KEY=your_key_here`
63
64	Python Dependencies:
65	- Python 3.7+
66	- `requests` (FMP API calls)
67	- `beautifulsoup4` (Finviz web scraping)
68	- `lxml` (HTML parsing)
69
70	Installation:
71	```bash
72	pip install requests beautifulsoup4 lxml
73	```
74
75	---
76
77	## Output
78
79	Output Directory: `reports/` (default) or custom via `--output-dir`
80
81	Generated Files:
82	- `canslim_screener_YYYY-MM-DD_HHMMSS.json` - Structured data for programmatic use
83	- `canslim_screener_YYYY-MM-DD_HHMMSS.md` - Human-readable report
84
85	Report Contents:
86	- Market Condition Summary (trend, M score, warnings)
87	- Top N CANSLIM Candidates (ranked by composite score)
88	- Component Breakdown for each stock (C, A, N, S, L, I, M scores with details)
89	- Rating interpretation (Exceptional+/Exceptional/Strong/Above Average)
90	- Quality warnings and data source notes
91	- Summary statistics (rating distribution)
92
93	Rating Bands:
94	- Exceptional+ (90-100): All components near-perfect, aggressive buy
95	- Exceptional (80-89): Outstanding fundamentals + momentum, strong buy
96	- Strong (70-79): Solid across components, standard buy
97	- Above Average (60-69): Meets thresholds with minor weaknesses, buy on pullback
98
99	---
100
101	## Workflow
102
103	### Step 1: Verify API Access and Requirements
104
105	Check if user has FMP API key configured:
106
107	```bash
108	# Check environment variable
109	echo $FMP_API_KEY
110
111	# If not set, prompt user to provide it
112	```
113
114	Requirements:
115	- FMP API key (free tier: 250 calls/day, sufficient for 40 stocks)
116	- Python 3.7+ with required libraries:
117	- `requests` (FMP API calls)
118	- `beautifulsoup4` (Finviz web scraping)
119	- `lxml` (HTML parsing)
120
121	Installation:
122	```bash
123	pip install requests beautifulsoup4 lxml
124	```
125
126	If API key is missing, guide user to:
127	1. Sign up at https://site.financialmodelingprep.com/developer/docs
128	2. Get free API key (250 calls/day)
129	3. Set environment variable: `export FMP_API_KEY=your_key_here`
130
131	### Step 2: Determine Stock Universe
132
133	Option A: Default Universe (Recommended)
134	Use top 40 S&P 500 stocks by market cap (predefined in script):
135
136	```bash
137	python3 skills/canslim-screener/scripts/screen_canslim.py
138	```
139
140	Option B: Custom Universe
141	User provid

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