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.

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.

See Example Outputs

These visual excerpts use fictional data to show the kinds of results you can review before setting up a skill. They are illustrations, not live market readings or trading instructions.

Select a preview to open the full-size SVG; on a phone, zoom after opening.

Choose a workflow: Trading Skills Navigator recommends a starting path from your goal.

Review market risk: The market-regime-daily workflow ends with an Exposure Coach posture for human review, not an order.

Learn from closed trades: Weekly Performance Digest summarizes realized outcomes and process lessons.

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 (6 skillsets shipped: market-regime, core-portfolio, dividend-income, swing-opportunity, trade-memory, strategy-research; consumed by the Navigator).

Getting Started

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

See the Changelog for changes and the release compatibility and migration policy before updating an installed skill.

Use with Claude Web App

1. Open the [latest GitHub Release](https://github.com/tradermon