Getting it into your agent
It runs from inside its repository, so the clone comes first — what it calls does not travel with the file alone.
git clone --depth 1 https://github.com/mphinance/alpha-skillsnpx agentmods add skills/mphinance/alpha-skills/canslim-screenerWrote 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/mphinance/alpha-skills/canslim-screener)<a href="https://agentmods.dev/skills/mphinance/alpha-skills/canslim-screener"><img src="https://agentmods.dev/badge/skills/mphinance/alpha-skills/canslim-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/mphinance/alpha-skills/canslim-screener"><img src="https://agentmods.dev/badge/skills/mphinance/alpha-skills/canslim-screener.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.00060 | $0.06398 |
| Opus 5 | $0.00030 | $0.03199 |
| Sonnet 5 | $0.00012 | $0.01280 |
| Haiku 4.5 | $0.00006 | $0.00640 |
Grade A, and why
canslim-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 11d 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.
This is a copy
88% identical to canslim-screener — 43 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 645 lines — stays where its author put it; the contents beside it link to each section on GitHub.
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:
- Stage 1 (FMP API + Finviz): Analyze stock universe with all 7 CANSLIM components
- 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 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%
- I (Institutional): 10%
- M (Market Direction): 5%
Future Phases:
- Phase 4: FINVIZ Elite integration → 10x faster execution
When to Use This Skill
Explicit Triggers:
- "Find CANSLIM stocks"
- "Screen for growth stocks using O'Neil's method"
- "Which stocks have strong earnings and momentum?"
- "Identify stocks near 52-week highs with accelerating earnings"
- "Run a CANSLIM screener on [sector/universe]"
Implicit Triggers:
- User wants to identify multi-bagger candidates
- User is looking for growth stocks with proven fundamentals
- User wants systematic stock selection based on historical winners
- User needs a ranked list of stocks meeting O'Neil's criteria
What ships with it
21 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.
- README.md 24 KB
- references/canslim_methodology.md 25 KB
- references/fmp_api_endpoints.md 19 KB
- references/interpretation_guide.md 17 KB
- references/scoring_system.md 20 KB
- scripts/calculators/earnings_calculator.py 14 KB runs code
- scripts/calculators/growth_calculator.py 11 KB runs code
- scripts/calculators/institutional_calculator.py 13 KB runs code
- scripts/calculators/leadership_calculator.py 13 KB runs code
- scripts/calculators/market_calculator.py 7.8 KB runs code
- scripts/calculators/new_highs_calculator.py 6.3 KB runs code
- scripts/calculators/supply_demand_calculator.py 7.8 KB runs code
- scripts/check_institutional_endpoint.py 3.9 KB runs code
- scripts/finviz_stock_client.py 7.0 KB runs code
- scripts/fmp_client.py 19 KB runs code
- scripts/report_generator.py 14 KB runs code
- scripts/scorer.py 21 KB runs code
- scripts/screen_canslim.py 13 KB runs code
- scripts/tests/conftest.py 412 B runs code
- scripts/tests/test_canslim_fixes.py 20 KB runs code
- scripts/tests/test_fmp_fallback.py 14 KB runs code
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.
- 11d ago First seen · 645 lines · 60 tokens per session scan A 55835c169e8f
canslim-screener is a skill published in the GitHub repository mphinance/alpha-skills (22 stars, last pushed 13d ago), licensed MIT. It adds 60 tokens to every session and 6,398 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 88% identical to canslim-screener, differing in 43 lines, and is treated as a copy.
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