Agent skill · data analytics · tradermonty
signal-postmortem
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.
Why this skill is useful
Provides domain-specific analysis and feedback mechanisms for trading signals that the AI wouldn't reliably generate on its own.
What it needs
Requires python installed locally. Requires fmp account access. About 3k tokens when loaded. Last updated 2026-08-06. 2,581 stars on the source repository.
What this skill does
Signal Postmortem Overview Signal Postmortem records and analyzes the outcomes of trading signals generated by the edge pipeline, screeners, and other skills. It compares predicted edge direction against 5-day and 20-day realized returns, categorizes outcomes (true positive, false positive, missed opportunity, regime mismatch), and generates feedback for edge-signal-aggregator weight adjustments and skill improvement backlog entries. When to Use After a trade has been closed and you want to record the outcome When reviewing a batch of signals that have reached their holding period (5 or 20 days) To identify systematic false positive patterns from specific skills To generate feedback for edge-signal-aggregator weight calibration When building a skill improvement backlog from decision quality metrics For periodic (weekly/monthly) signal quality audits Prerequisites Python 3.9+ FMP API key (optional, for fetching realized returns if not provided manually) Standard library + requests for API calls Input: signal records in JSON format (from edge-signal-aggregator or screener outputs) API Key Setup (Optional) If you want to automatically fetch price data for return calculations, set up the FMP API key: Alternatively, pass the key via command line with --api-key YOURKEY. Without an API key, you can still record outcomes manually by providing --exit-price and --exit-date. Workflow Step 1: Prepare Signal Records Gather closed or matured signal records. Each record should include: signalid: Unique identifier ticker: Stock symbol signaldate: Date signal was generated predicteddirection: LONG or SHORT sourceskill: Which skill generated the signal entryprice: Price at signal generation (optional, for manual override) Step 2: Record Outcomes Run the postmortem recorder to fetch realized returns and classify outcomes. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills tradermonty/signal-postmortem