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
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add tradermonty/claude-trading-skills --skill stockbee-setup-fluency-trainergit clone --depth 1 https://github.com/tradermonty/claude-trading-skillsWrote 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/stockbee-setup-fluency-trainer)<a href="https://agentmods.dev/skills/tradermonty/claude-trading-skills/stockbee-setup-fluency-trainer"><img src="https://agentmods.dev/badge/skills/tradermonty/claude-trading-skills/stockbee-setup-fluency-trainer/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/stockbee-setup-fluency-trainer"><img src="https://agentmods.dev/badge/skills/tradermonty/claude-trading-skills/stockbee-setup-fluency-trainer.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 | $0.00098 | $0.01386 |
| Opus 5.5 | $0.00039 | $0.00554 |
| Sonnet 5.5 | $0.00020 | $0.00277 |
| Haiku 4.5 | $0.00010 | $0.00139 |
Grade A, and why
stockbee-setup-fluency-trainer 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 today.
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
1 near-identical copy found in the catalogue:
- stockbee-setup-fluency-trainer — 100% identical, 13 lines differ
How it starts
The opening of the file, as written. The whole thing — 136 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Stockbee Setup Fluency Trainer
Build and maintain a model book for Stockbee-style Momentum Burst setups. This skill turns daily screener candidates into structured study records, updates them after the 3-day and 5-day windows mature, and summarizes which setup features are working or failing.
When to Use
- User wants to study Stockbee Momentum Burst setups systematically
- User asks to build a model book from
stockbee-momentum-burst-screeneroutput - User wants to review failed candidates, missed trades, or A/B setup quality
- User wants 3-day / 5-day forward returns, MFE, MAE, and stop-hit outcomes
- User wants to improve setup recognition before increasing position size
- User asks which Stockbee tags should be promoted, downgraded, or filtered
Prerequisites
- Python 3.10+
- A
stockbee-momentum-burst-screenerJSON report, or compatible candidate JSON - Optional: FMP API key for outcome updates when offline OHLCV JSON is not supplied
- Recommended local state path:
state/stockbee/model_book.jsonl
Workflow
Step 1: Ingest Momentum Burst Candidates
Run after the Stockbee Momentum Burst screener has produced a JSON report.
python3 skills/stockbee-setup-fluency-trainer/scripts/build_model_book.py ingest \
--screener-json reports/stockbee_momentum_burst_YYYY-MM-DD_HHMMSS.json \
--model-book state/stockbee/model_book.jsonl \
--output-dir reports/
Use --include-rejects when intentionally building a negative-example set. Otherwise rejected candidates are skipped.
Step 2: Update 3-Day and 5-Day Outcomes
Use FMP:
python3 skills/stockbee-setup-fluency-trainer/scripts/build_model_book.py update \
--model-book state/stockbee/model_book.jsonl \
--horizons 3,5 \
--output-dir reports/
Use offline OHLCV JSON:
python3 skills/stockbee-setup-fluency-trainer/scripts/build_model_book.py update \
--model-book state/stockbee/model_book.jsonl \
--prices-json data/daily_ohlcv.json \
--horizons 3,5 \
--output-dir reports/
What ships with it
8 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/model_book_schema.md 2.5 KB
- references/outcome_tags.md 1.6 KB
- references/review_workflow.md 2.3 KB
- requirements.txt 128 B
- scripts/build_model_book.py 38 KB runs code
- scripts/fmp_client.py 20 KB runs code
- scripts/tests/test_build_model_book_coverage.py 43 KB runs code
- scripts/tests/test_build_model_book.py 6.7 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.
- today Changed · +13 lines 34b5af5b9d85
- 1mo ago First seen · 123 lines · 98 tokens per session scan A ae45d220f94c
stockbee-setup-fluency-trainer is a skill published in the GitHub repository tradermonty/claude-trading-skills (3,332 stars, last pushed yesterday), licensed MIT. It adds 98 tokens to every session and 1,386 once invoked, about $0.0004 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 2026-09-03.
Other skills, from other repositories
financial-statement-explainer
Explain a financial statement (P&L, balance sheet, or cash flow) in plain English. Use when asked to explain a P&L / income statement, a balance sheet, a cash flow statement, or to make financials understandable to a non-finance reader. Produces a plain-language walkthrough — what each section means, the line items…
learning-coach
Explains any InvestSkill output like a mentor — every metric in plain words, why it matters, its good / bad range, and the lesson that teaches it — then asks 3–5 Socratic questions and "what would change your mind?". --level beginner / intermediate, --lang zh-TW, and a --quiz mode that drills a Learning lesson.
trading-manual-writer
A writing skill for creating sections of a trading manual for beginners and individual investors. It explains financial instruments or trading topics in Markdown and can include SVG illustrations.
market-microstructure-traditional
Traditional market microstructure concepts applied to crypto — order book dynamics, market making theory, price formation models, execution quality measurement, and CEX vs DEX structural differences.
finance-econ-literacy
A Korean-language guide to understanding economic indicators such as interest rates, exchange rates, inflation, GDP, employment, and trade. It explains how these figures can affect loans, savings, investments, and spending.
okx-activity
Register for the OKX.AI Trading Hackathon or explain its entry requirements and eligibility. Trigger on requests in any language to register, sign up, join, enter, or participate in the hackathon. Registers an existing Trading ASP; never creates one.