runtime-log-forensics

What problem does it solve?

This Skill eliminates guesswork when debugging runtime anomalies in the CryptoMaster cryptocurrency trading bot, requiring all claims to be tied to concrete log lines, state snapshots, and code execution paths to avoid incorrect root cause assumptions.

Core Features & Use Cases

• Evidence Collection: Pulls timestamped data from journalctl systemd logs, JSON position snapshots, SQLite trade records, and relevant source code paths for the trading bot.
• Timeline Reconstruction: Builds precise UTC timelines of trading events to pinpoint exactly when anomalies like unexpected position closures or state corruption occurred.
• Fact/Hypothesis Separation: Strictly distinguishes verified observable facts from unproven inferences to ensure forensic findings are accurate and actionable.
• Use Case: If your paper trading positions are closing earlier than their configured timeout, this Skill can correlate log timestamps, position state files, and trade executor code to identify if the wrong timeout variable is being used.

Quick Start

Use the runtime-log-forensics skill to investigate why my CryptoMaster paper positions are closing 10 minutes earlier than their configured 30-minute timeout, pulling journalctl logs, position snapshots, and the relevant trade executor code to find the exact root cause.