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
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/tradermonty/claude-trading-skillsnpx agentmods add skills/tradermonty/claude-trading-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/tradermonty/claude-trading-skills/canslim-screener)<a href="https://agentmods.dev/skills/tradermonty/claude-trading-skills/canslim-screener"><img src="https://agentmods.dev/badge/skills/tradermonty/claude-trading-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/tradermonty/claude-trading-skills/canslim-screener"><img src="https://agentmods.dev/badge/skills/tradermonty/claude-trading-skills/canslim-screener.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk pass
- 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 | $0.00060 | $0.06829 |
| Opus 5.5 | $0.00024 | $0.02732 |
| Sonnet 5.5 | $0.00012 | $0.01366 |
| Haiku 4.5 | $0.00006 | $0.00683 |
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 1mo 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
3 near-identical copies found in the catalogue:
- canslim-screener — 100% identical, 0 lines differ
- canslim-screener — 100% identical, 0 lines differ
- canslim-screener — 88% identical, 43 lines differ
How it starts
The opening of the file, as written. The whole thing — 672 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 3.1 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:
Weighted RS = 0.40 × rel_3m + 0.30 × rel_6m + 0.30 × rel_12m
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:
- No benchmark → weighted absolute stock performance + 20% penalty.
- 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).
- <50 bars of price history → score=0 with
errorset.
What ships with it
26 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.
- 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
- requirements.txt 301 B
- scripts/calculators/earnings_calculator.py 14 KB runs code
- scripts/calculators/growth_calculator.py 11 KB runs code
- scripts/calculators/institutional_calculator.py 15 KB runs code
- scripts/calculators/leadership_calculator.py 24 KB runs code
- scripts/calculators/market_calculator.py 8.2 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 3.0 KB runs code
- scripts/finviz_stock_client.py 7.0 KB runs code
- scripts/fmp_client.py 25 KB runs code
- scripts/report_generator.py 19 KB runs code
- scripts/scorer.py 21 KB runs code
- scripts/screen_canslim.py 19 KB runs code
- scripts/tests/conftest.py 412 B runs code
- scripts/tests/test_canslim_calculators_coverage.py 39 KB runs code
- scripts/tests/test_canslim_coverage.py 71 KB runs code
- scripts/tests/test_canslim_fixes.py 21 KB runs code
- scripts/tests/test_fmp_fallback.py 17 KB runs code
- scripts/tests/test_fmp_stable_migration.py 5.2 KB runs code
- scripts/tests/test_institutional_fallback.py 4.4 KB runs code
- scripts/tests/test_leadership_rs.py 20 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.
- 1mo ago First seen · 672 lines · 60 tokens per session scan A e2450caba733
canslim-screener is a skill published in the GitHub repository tradermonty/claude-trading-skills (3,373 stars, last pushed yesterday), licensed MIT. It adds 60 tokens to every session and 6,829 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-08-30.
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