claude-trading-skills

Claude Trading Skills

Claude Trading Skills started as a personal project to use AI to improve my own trading process.

Claude Trading Skills is a Claude Skills-based trading workflow toolkit for time-constrained individual investors.

It is designed for investors who use long-term investing, ETFs, and dividend stocks as their core, while using disciplined swing trading as a satellite strategy when market conditions are favorable.

The goal is not to outsource buy/sell decisions to AI. The goal is to structure market review, risk management, trade planning, journaling, and continuous improvement. It is open source because the workflows, checklists, and review habits behind better trading decisions can improve through shared practice.

This is not a signal service or a promise of profitability. It is a toolkit for traders who want to build a better decision process.

The project follows a first for self, open for others stance: it is built first as a practical workflow the author uses, then shared openly for others who face similar constraints.

Documentation site: https://tradermonty.github.io/claude-trading-skills/

Project vision: PROJECT_VISION.md

日本語版READMEはREADME.ja.mdをご覧ください。

Disclaimer

This repository is for educational, research, and process-improvement purposes only. It is not financial advice, investment advisory service, tax advice, legal advice, a signal service, or a broker execution platform. Trading and investing involve risk, including loss of principal. Past performance, backtests, screens, reports, and AI-generated analysis do not guarantee future results. All trading decisions, position sizing, tax/regulatory compliance, and broker usage are the user's responsibility.

The project is provided under the MIT License, AS IS, WITHOUT WARRANTY.

Who This Is For

This repository is designed for:

• Time-constrained individual investors
• Long-term investors who also want disciplined swing-trading upside
• Dividend and ETF investors who want structured portfolio review
• Traders who want to manage risk before finding trade candidates
• Investors who want to journal and improve their decision process

It is not designed for fully automated trading, signal outsourcing, or short-term scalping.

Recommended Starting Path

New users should start with one of these operational workflows. Each link points to a machine-readable manifest under workflows/ that names the exact skills, decision gates, and artifacts in order.

Goal	Workflow	Anchor Skills	API Profile
15-minute daily market check	market-regime-daily	market-breadth-analyzer, uptrend-analyzer, exposure-coach	No API for basic path
Weekly long-term portfolio review	core-portfolio-weekly (sample)	portfolio-manager, kanchi-dividend-review-monitor, trader-memory-core	Alpaca required; manual CSV is a degraded fallback
Find swing candidates only when risk is allowed	swing-opportunity-daily (sample)	vcp-screener, drawdown-circuit-breaker, technical-analyst, position-sizer, trader-memory-core, pre-trade-discipline-gate	FMP for screeners; local state for risk and discipline gates
Record and learn from every closed trade	trade-memory-loop	trader-memory-core, signal-postmortem	No API for manual path
Review monthly performance and adjust rules	monthly-performance-review (sample)	trader-memory-core, signal-postmortem, backtest-expert	No API for manual path

See workflows/README.md for how to read a manifest and run it manually. For a one-page "which workflow fits my situation?" guide, see Find Your Workflow (日本語).

New here? Follow Your First Week (日本語) from installation through a no-paid-data-API market check, first journal entry, and first weekly review.

What This Actually Costs

Claude Web Skills are currently available on Free, Pro, Max, Team, and Enterprise accounts; see Anthropic's current Skills help because access can change. Claude Code has separate account requirements, and the Claude.ai Free plan does not include it; see the Claude Code setup guide. FMP, FINVIZ Elite, and Alpaca are optional data or broker integrations for specific workflows. The five-skill starter path below works with public CSVs, chart screenshots, and local files, so it does not require a paid market-data API subscription.

No API Key Starter Path

If you do not have FMP / FINVIZ / Alpaca subscriptions, start with these five skills and run them manually:

1. market-breadth-analyzer — public CSV breadth scoring; no API key
2. uptrend-analyzer — public CSV uptrend participation; no API key
3. position-sizer — pure calculation; no I/O
4. trader-memory-core — local YAML journaling
5. signal-postmortem — review framework

This path lets you review market conditions, size trades, journal decisions, and review outcomes without paid data APIs. Note: "no API" does not mean "no external data" — these skills still need public CSVs, chart screenshots, or local files. See each skill's integrations: entry in skills-index.yaml for exact input requirements.

Canonical source: skills-index.yaml is the authoritative index of all skills. If this README, CLAUDE.md, or docs disagree with the index, the index is correct. The same applies to multi-skill workflows — workflows/*.yaml is canonical.

Repository Layout

• skills/<skill-name>/ – Source folder for each trading skill. Contains SKILL.md, reference material, and any helper scripts.
• skills-index.yaml – Canonical metadata index for every skill (id, category, integrations, workflows back-references).
• workflows/ – Operational workflow manifests for the Core + Satellite routines (canonical, validator-enforced via --strict-workflows).
• skill-packages/ – Pre-built .skill archives ready to upload to Claude's web app Skills tab.
• docs/ – Documentation site content, generated skill pages, and docs/dev/metadata-and-workflow-schema.md (schema spec).
• scripts/ – Repository-level automation, including the schema validator and one-shot bootstrap helper.
• skillsets/ – Purpose-specific install bundles defining required / recommended / optional skills for major goals (4 core skillsets shipped: market-regime, core-portfolio, swing-opportunity, trade-memory; consumed by the Navigator).

Getting Started

First time here? Read the FAQ for plan, cost, safety, and scope answers.

Use with Claude Web App

1. Download the .skill file that matches the skill you want from skill-packages/.
2. For an individual account, open Settings > Capabilities and enable Code execution and file creation. Team and Enterprise users may need an organization owner to enable Skills.
3. Open Customize > Skills, upload the ZIP, confirm it appears in the list, and enable it if needed (see Anthropic's current Skills help).

Use with Claude Code (desktop or CLI)

1. Clone or download this repository.
2. Copy the desired skill folder (e.g., backtest-expert) to ~/.claude/skills/ for personal use or .claude/skills/ inside a project (see the Claude Code setup guide).
3. Claude Code detects changes in an existing skills directory. Restart it only if you created the top-level skills directory after the session started.

Tip: .skill packages are built from the source folders with tests and local build artifacts omitted. Edit a source folder if you want to customize a skill, then run python3 scripts/package_skills.py --skill <skill-name> before uploading to the web app.

Supported platforms

The project supports Python 3.9 to 3.13 on Linux, Windows, and macOS. A combination counts as supported only if it is exercised by the project's CI; other combinations in that range are best-effort and unverified. See docs/dev/compatibility-matrix.md for the exact supported matrix and how it is enforced.

Companion Work Package

Want a ready-to-run agent-style workflow? See the companion Hermes Trading Research Agent Work Package.

It packages these skills into a Hermes profile with task-oriented slash-command routines such as /pre-market-routine, /after-close-review, /trade-journal, /weekly-portfolio-review, and /monthly-performance-review.

This is a research, journaling, and risk-review assistant, not an automated trading system. It does not place orders, provide a signal service, or run hidden scheduled jobs; human decision gates remain central.

Core Skill Areas

This repository contains skills across the following areas:

Area	Example Skills
Market Regime	market-breadth-analyzer, uptrend-analyzer, exposure-coach
Core Portfolio	portfolio-manager, value-dividend-screener, kanchi-dividend-sop
Swing Opportunities	vcp-screener, canslim-screener, breakout-trade-planner
Trade Planning	position-sizer, technical-analyst, pre-trade-discipline-gate
Trade Memory	trader-memory-core, signal-postmortem
Strategy Research	backtest-expert, manifoldbt-backtester, edge-pipeline-orchestrator
Advanced Satellite	parabolic-short-trade-planner, earnings-trade-analyzer, options-strategy-advisor

The detailed catalog below is auto-generated from skills-index.yaml by scripts/generate_catalog_from_index.py. To update a skill's description, edit its skills-index.yaml entry and re-run the generator (python3 scripts/generate_catalog_from_index.py). For a more navigable version, use the documentation site. For an auto-generated overview of skill lifecycle, test coverage, and runtime health, see the Quality Dashboard.

Detailed Skill Catalog

Market Regime

Skill	Summary	Integrations	Role	Status
Breadth Chart Analyst (breadth-chart-analyst)	This skill should be used when analyzing market breadth charts, specifically the S&P 500 Breadth Index (200-Day MA based) and the US Stock Market Uptrend Stock Ratio charts.	chart_image required	standalone	production
COT Contrarian Detector (cot-contrarian-detector)	Detects crowded speculative (large-speculator) positioning in CFTC futures markets using Commitment of Traders data, implementing step 1 of Jason Shapiro's contrarian methodology.	fmp required	workflow_step	production
Crypto Regime Analyzer (crypto-regime-analyzer)	Quantifies crypto market regime health (0-100 composite, 100 = risk-on) from six components using free keyless public data.	coingecko required, binance_funding recommended, prices_json optional	standalone	beta
Downtrend Duration Analyzer (downtrend-duration-analyzer)	Analyze historical downtrend durations and generate interactive HTML histograms showing typical correction lengths by sector and market cap.	local_calculation —	research_only	production