Backtest Expert
Expert guidance for systematic backtesting of trading strategies. Use when developing, testing, stress-testing, or validating quantitative trading strategies. Covers "beating…
Finance & Trading
tradermonty3.6k
Record and analyze post-trade outcomes for signals generated by edge pipeline and other skills. Track false positives, missed opportunities, and regime mismatches. Feed results back to edge-signal-aggregator weights and skill improvement backlog.
Install
Research and analysis tools, not financial advice. Some workflows use optional FMP, FINVIZ Elite or Alpaca accounts; the repo's five-skill starter path needs no API key. Open the repository
Run this in your project folder. It works with Claude Code, Cursor, Codex and dozens of other agents.
$ npx skills add tradermonty/claude-trading-skills --skill signal-postmortemNeeds Node.js. Add -g to install for every project, or -a claude-code to skip the agent picker.
How to use Signal Postmortem
Once it's installed, Claude reads this skill on its own whenever a request matches what it's for, so you don't have to mention it by name. In Claude Code you can also run it directly by typing /signal-postmortem.
It includes scripts that Claude may run on your computer, so skim them on GitHub before you install.
What the instructions cover
- 1Overview
- 2When to Use
- 3Prerequisites
- 4Workflow
- 5Output Format
- 6Resources
- 7Key Principles
Section headings from the skill's SKILL.md file.
What's inside · 10 files
- SKILL.md
- references/feedback-integration.md
- references/outcome-classification.md
- requirements.txt
- scripts/postmortem_analyzer.py
- scripts/postmortem_recorder.py
- scripts/tests/conftest.py
- scripts/tests/test_cli_workflow.py
- scripts/tests/test_postmortem_analyzer.py
- scripts/tests/test_postmortem_recorder.py
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