compound

Analyze losing trades to classify failures and generate knowledge-base entries.

Updated Apr 14, 2026
One-click install
npx skills add https://github.com/raosuraj23/alpaca-bot --skill compound-raosuraj23
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: compound
Source: https://github.com/raosuraj23/alpaca-bot/tree/main/.claude/skills/compound
Command: npx skills add https://github.com/raosuraj23/alpaca-bot --skill compound-raosuraj23

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes scripts (resource) and references (resource) components.

What problem does it solve?

Compound learning — post-mortem analysis of losing trades writes lessons to knowledge base, feeds back into scan and research.

Core Features & Use Cases

  • Post-mortem analysis for every loss to extract root causes and generate knowledge-base entries.
  • Integrates with Reflection Engine and nightly consolidation to update failure_log.jsonl and metrics_log.jsonl.
  • Supports deterministic classification and structured KB entries for long-term calibration.

Quick Start

Analyze each losing trade to generate a KB entry and refine strategy parameters.

Frequently Asked Questions about compound

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

FAQPage Schema
How do I automate post-mortem analysis for losing trades?▼

Automating post-mortem analysis for losing trades classifies failures deterministically and generates structured knowledge-base entries to refine your trading strategy. It extracts root causes from each loss to update failure logs and risk guardrails.

What is deterministic failure classification in trading analysis?▼

Deterministic failure classification in trading analysis systematically categorizes losing trades to extract actionable lessons. It formats these insights into knowledge-base entries using Haiku-based formatting for long-term strategy calibration.

How do I generate knowledge-base entries from trading losses?▼

To generate knowledge-base entries from trading losses, the system applies Haiku-based KB formatting to extract and structure root causes. This creates actionable lessons for nightly consolidation and strategy adjustment.

Can I integrate post-mortem analysis with an automated trading backend?▼

Yes, you can integrate post-mortem analysis with automated trading backends, live trader desks, and simulated environments. It connects with backend knowledge logs, updates metrics_log.jsonl, and triggers risk guardrail adjustments.

What's the best way to consolidate trading analysis logs nightly?▼

The best way to consolidate trading analysis logs nightly uses a Reflection Engine to aggregate daily post-mortem entries. It updates failure_log.jsonl and generates summaries to prompt strategy parameter adjustments.

How does post-mortem analysis feed into risk management guardrails?▼

Post-mortem analysis feeds into risk management by extracting root causes from losses and writing them to a knowledge base. These entries trigger prompts to adjust strategies and update risk guardrails for future trades.