canslim-screener

canslim-screener is a skill for Claude Code, Codex from tradermonty/claude-trading-skills. It costs 60 tokens per session (6,829 once invoked), scanned A, original, MIT.

A stock-screening skill based on CANSLIM, William O'Neil's method for finding growth stocks using earnings, growth, price momentum, ownership, and overall market direction.

In plain words
What is it for?
Use it to screen stocks, combine the seven CANSLIM factors into scores, filter for weak market conditions, and produce JSON or Markdown reports.
Why use it?
It narrows a large group of US stocks into ranked candidates using the same set of investment checks.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Needs its repository: it reads a path above its own folder, which exists only inside the repository. The line is --output-dir ../../../.

Good fit Use it to screen stocks, combine the seven CANSLIM factors into scores, filter for weak market conditions, and produce JSON or Markdown reports.

Compare 6 skills from other repositories ↓
About the project

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.

tradermonty/claude-trading-skills · 3,373 stars · on GitHub · tradermonty.github.io

Install

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.

Clone the repo
git clone --depth 1 https://github.com/tradermonty/claude-trading-skills
agentmods
npx agentmods add skills/tradermonty/claude-trading-skills/canslim-screener

Made for: Claude Code, Codex.

Wrote 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.

agentmods badge for canslim-screener

README.md
[![agentmods](https://agentmods.dev/badge/skills/tradermonty/claude-trading-skills/canslim-screener/github.svg)](https://agentmods.dev/skills/tradermonty/claude-trading-skills/canslim-screener)
Your own site
<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.

agentmods 80×15 button for canslim-screener

Your own site · 80×15
<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>
Per session 60 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 6,829 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • Socket pass 19 Sept 2026
  • Snyk pass 19 Sept 2026
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce 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

Measured 1mo ago against content hash e2450caba733, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

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.

The scan reads SKILL.md. This mod also ships 21 executable files (scripts/calculators/earnings_calculator.py, scripts/calculators/growth_calculator.py, scripts/calculators/institutional_calculator.py, …), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

Origin

Copies of this mod

3 near-identical copies found in the catalogue:

skills/canslim-screener/SKILL.md · 672 lines

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:

  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:

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:

  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.

Read the full file on GitHub · 672 lines

Files

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.

Changes

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.

  1. 1mo ago First seen · 672 lines · 60 tokens per session scan A e2450caba733

Subscribe to this mod's changes

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.

Related

Other skills, from other repositories

sector-rotation

An analysis framework for comparing industries in the Chinese A-share stock market, using business conditions, price momentum, valuation, and money flows. It produces rankings and higher- or lower-allocation suggestions.

HKUDS/Vibe-Trading · 39 tokens

twitter-reader

Read Twitter/X for financial research through opencli: the user's home timeline, tweet search, trending topics, bookmarks, a user's recent tweets, threads, articles, profiles, followers and following, and notifications. Use this skill whenever the user wants to know what people are saying on Twitter/X or fintwit about…

himself65/finance-skills · 110 tokens

energy-procurement

Codified expertise for electricity and gas procurement, tariff optimization, demand charge management, renewable PPA evaluation, and multi-facility energy cost management. Informed by energy procurement managers with 15+ years experience at large commercial and industrial consumers. Includes market structure analysis…

hashgraph-online/awesome-codex-plugins · 93 tokens

airdrop-hunting-guide

Guide to finding and qualifying for crypto airdrops — eligibility criteria, farming strategies, on-chain activity requirements, Sybil detection avoidance, and tracking tools. Use when helping users understand airdrops, check eligibility, or plan participation strategies.

nirholas/three.ws · 54 tokens

china-portfolio-monitoring

A monitoring framework for tracking the financial results, operating measures, strategic milestones, and risks of companies held by China-focused private-equity funds. It uses measures such as revenue growth, margins, debt, cash flow, and return on equity.

jwangkun/claude-for-financial-services-cn · 86 tokens

multi-expert-analyzer

A method for examining complicated questions through several expert viewpoints, followed by fact-checking and criticism.

digoal/blog · 292 tokens