skills.rest
darkounus90
darkounus90COMMUNITY
Explore all skills by this author →
GitHub

signal-postmortem

Record trading signal outcomes and generate feedback for edge-signal-aggregator calibration.

1|Updated Feb 18, 2026
Search Tags:#skill improvement#signal analysis#edge-signal-aggregator#trading postmortem#trading feedback
One-click install
npx skills add https://github.com/darkounus90/BOTTX3 --skill signal-postmortem-darkounus90
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: signal-postmortem
Source: https://github.com/darkounus90/BOTTX3/tree/main/.agents/skills/signal-postmortem
Command: npx skills add https://github.com/darkounus90/BOTTX3 --skill signal-postmortem-darkounus90

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires requests, datetime, json, and includes scripts (resource) and references (resource) and assets (resource) components.

What problem does it solve?

This Skill provides a framework to analyze trading signals after execution, feeding insights back to improve skill quality and edge-signal-aggregator weights.

Core Features & Use Cases

  • Postmortem Recording: Record outcomes of closed and matured trading signals.
  • Outcome Classification: Classify outcomes into categories such as TRUE_POSITIVE, FALSE_POSITIVE, MISSED_OPPORTUNITY, and REGIME_MISMATCH.
  • Feedback Generation: Generate feedback files for edge-signal-aggregator weight calibration and skill improvement backlog entries.
  • Summary Reporting: Generate summary statistics and trend analysis reports by skill, ticker, and time period.

Quick Start

Record the post-mortem of a completed trade signal by using the command:

python3 skills/signal-postmortem/scripts/postmortem_recorder.py \
  --signal-id sig_aapl_20260310_abc \
  --exit-price 178.50 \
  --exit-date 2026-03-15 \
  --outcome-notes "Closed at target, +3.2% in 5 days"

Frequently Asked Questions about signal-postmortem

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I automate postmortem analysis for trading signals?▼

Automate trading signal postmortem analysis by recording post-trade outcomes, classifying results into categories like TRUE_POSITIVE or FALSE_POSITIVE, and generating feedback files to calibrate edge-signal-aggregator weights and improve skill quality.

What is signal outcome classification in trading feedback loops?▼

Signal outcome classification categorizes closed trading signals into TRUE_POSITIVE, FALSE_POSITIVE, MISSED_OPPORTUNITY, and REGIME_MISMATCH to close the feedback loop and generate actionable insights for edge-signal-aggregator weight calibration.

How do I record a postmortem for a matured trading signal using Python?▼

Record a matured trading signal postmortem using the postmortem_recorder.py script, providing the signal-id, exit-price, exit-date, and outcome-notes to capture post-trade outcomes for summary statistics and trend analysis.

Does signal-postmortem require a specific Python version or API key?▼

Signal-postmortem requires Python 3.9 or higher, an FMP API key, and standard libraries including requests, datetime, and json for executing API calls and processing trading signal data.

How are postmortem results used to improve trading signal performance?▼

Postmortem results improve trading signal performance by generating feedback files that create skill improvement backlog entries and calibrate edge-signal-aggregator weights based on summary statistics across skills, tickers, and time periods.

Can I generate trend analysis reports by ticker and time period for trading signals?▼

Generate summary statistics and trend analysis reports by skill, ticker, and time period by feeding closed trading signal postmortem data into the analysis framework to evaluate post-trade outcomes.

Related Skills

Explore More Finance & Accounting Skills→
IhsanDanish25IhsanDanish25
2

signal-postmortem

Analyze post-trade outcomes and classify trading signal results.

Community
Advanced
X-School-AcademyX-School-Academy
9

dev-swarm-code-review

Review implemented code against backlog requirements and generate improvement backlogs.

Official
Advanced
pasie15pasie15

signal-postmortem

Analyze trading signal outcomes and classify them into postmortem categories.

Community
Advanced
gracefullightgracefullight
43

backtesting-trading-strategies

Backtest trading strategies against historical data and export performance metrics.

Community
Advanced