GhostTrace: Forensic Autopsy & Counterfactual Debugger for Autonomous AI Agents
This is a submission for the Hacktoberfest Open-Source AI Challenge Week 4: Ghost in the Machine What I Built GhostTrace is an autonomous forensic autopsy platform and counterfactual debugger for AI agent workflows. The Problem: The "Ghost in the Machine" In modern multi-agent systems, agents don't
Hacktoberfest Open-Source AI Challenge: Ghost in the Machine Submission 👻🌼
This is a submission for the Hacktoberfest Open-Source AI Challenge Week 4: Ghost in the Machine
GhostTrace is an autonomous forensic autopsy platform and counterfactual debugger for AI agent workflows.
In modern multi-agent systems, agents don't simply crash with neat stack traces. They fail silently:
When an agent fails, developers are left sifting through megabytes of noisy, unformatted JSON telemetry logs at 2 AM. These elusive, silent failures are the true "Ghosts in the Machine".
GhostTrace solves this by ingesting raw agent telemetry, building deterministic causal dependency graphs, performing grounded counterfactual root-cause deduction with Google Gemma 2, and automatically synthesizing runnable Vitest regression suites with circuit-breaker assertions to guarantee that the phantom bug never returns to production.
Watch on YouTube: GhostTrace — Forensic Autopsy & Counterfactual Debugger for AI Agents
Evidence-backed, deterministic forensic debugger and root cause analyzer for AI agents. Built for the official DEV Challenge: Hacktoberfest 2026 Week 4 — "Ghost in the Machine".
🌐 Live Production Deployment: https://ghosttrace-s26u.onrender.com/
Figure: Interactive forensic dashboard featuring deterministic timeline reconstruction, causal anomaly detection, evidence-grounded Google Gemma 2 hypotheses, automated Vitest regression test generation, multi-tenant Auth0 login, and incident history persistence.
Modern AI agents are complex non-deterministic state machines. When agents fail—spinning in infinite tool loops, hallucinating invalid tool schema arguments, exceeding context windows, or corrupting session state—developers are left sifting through gigabytes of unstructured JSON telemetry.
GhostTrace is a developer-first forensic debugger that exorcises the "ghost in the machine". It ingests raw trace logs from any LLM agent framework (Mastra, LangChain, CrewAI, AutoGen, or custom runtimes), deterministically reconstructs a millisecond-precision waterfall timeline, detects causal anomalies, uses Google Gemma 2 …