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 simply crash with neat stack traces. They fail silently:

• Hallucinating non-existent database columns or invalid tool arguments.
• Trapped in recursive API reasoning loops while burning through millions of tokens.
• Suffering subtle state drift and context overflow.

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.

Demo

• 🌐 Live Cloud Application (Render): https://ghosttrace-s26u.onrender.com/
• 🎥 Video Walkthrough:

Watch on YouTube: GhostTrace — Forensic Autopsy & Counterfactual Debugger for AI Agents

Key Live Features

1. Interactive Trace Waterfall: Millisecond-precision timeline detailing token usage, tool latency, and exact error offsets.
2. Causal Anomaly Engine: Real-time detection of infinite loops, unhandled tool errors, and context window saturation.
3. Google Gemma 2 Hypothesis Card: Deterministic root-cause analysis with strict Event-ID grounding ([evt_104], [evt_108]), completely eliminating hallucinated diagnoses.
4. Anti-Regression Vitest Synthesizer: One-click copy-pasteable TypeScript test suite verifying circuit breakers and schema resilience.

Code

• GitHub Repository: https://github.com/diusazzad/ghosttrace
• Open-Source License: MIT
• Test Suite: 18 test files, 162 passing tests (100% pass rate) with zero TypeScript errors.

How I Built It

GhostTrace is engineered strictly around open-source AI and transparent agent architecture:

flowchart TD A[Raw Agent Telemetry / Sentry OTEL / JSON] --> B[Mastra Core Workflow Ingestion] B --> C[Stage 1: Deterministic Causal Graph & Loop Anomaly Detector] C --> D[Stage 2: Google Gemma 2 9B Counterfactual Inference Engine] D --> E[Stage 3: Evidence Grounding & Anti-Hallucination Guard] E --> F[Stage 4: Automated Vitest Regression Test Synthesis] F --> G[Interactive Next.js 16 Dark-Mode Forensic Dashboard] G --> H[Auth0 Tenant Isolation & MongoDB Atlas Persistence]

1. Workflow Orchestration (Mastra Core v1.80.0): A resilient 4-stage pipeline orchestrating telemetry parsing, structural failure detection, graph topology construction, and automated test synthesis.
2. Open-Weight Counterfactual AI (Google Gemma 2 9B): Runs inference with strict prompt constraints requiring Event-ID citations, performing grounded counterfactual deduction without proprietary vendor lock-in.
3. Observability & Agent Tracing (Sentry Agent Tracing): Live OpenTelemetry GenAI spans capturing latency, tokens, error breadcrumbs, and step-level agent actions.
4. Data Isolation & Persistence (MongoDB Atlas): Enterprise multi-tenant database tier enforcing compound unique constraints (ownerId_1_traceId_1) and owner isolation.
5. Zero-Trust Agent Auth (Auth0 v4): Server-side identity verification ensuring anonymous users can never access or leak sensitive agent execution history.

Why Does Open Innovation Matter?

1. Privacy & Proprietary Trace Protection: Agent traces frequently contain API keys, confidential customer data, internal system prompts, and proprietary database schemas. Closed commercial APIs require sending raw traces to third-party cloud servers. GhostTrace allows entire organizations to run forensic investigations completely on-premises with open-weight models.
2. Deterministic Reproducibility: Closed APIs change weights and prompt behaviors behind the scenes. Open-weight models like Gemma and open frameworks like Mastra and Temporal ensure that a forensic finding diagnosed today will yield the exact same deterministic autopsy results tomorrow.
3. No Per-Investigation Toll: Large agent teams execute thousands of trace autopsies daily; open innovation eliminates crippling token billing for debugging infrastructure.

Prize Categories

We are entering the following categories:

Featured Categories ($200)

• Best Use of Gemma: Running google/gemma-2-9b-it for counterfactual hypothesis deduction and rule-based grounding defense.
• Best Use of TabPFN: Tabular foundation model integration for anomaly prediction and trace metric classification.

Partner Categories ($100)

• Best Use of Auth0 for AI Agents: Enforcing multi-tenant session verification and owner-isolated data access.
• Best Use of MongoDB Atlas: Verified live Atlas cluster with compound indexing, unique collision detection, and owner scoping.
• Best Use of Sentry Agent Tracing: Live OpenTelemetry GenAI spans, agent action breadcrumbs, and real-time cloud event delivery.
• Best Use of Mastra: 4-step Mastra Core resilient agent workflow orchestration.
• Best Use of Entire: Entire CLI session capture, Git checkpoint refs, and immutable commit audit trails.
• Best Use of Ultramarine: Ultramarine-1-flash provider integration with token cost calculation and structured Zod output.
• Best Use of Backboard: Backboard Studio provider integration with offline deterministic grounding defense.
• Best Use of Browserbase: Headless browser session replay and DOM state capture for web agent failures.
• Best Use of Temporal: Temporal durable execution engine with automatic activity retries and fault recovery.
• Best Use of Tiger Data: Forensic knowledge graph and vector similarity search for historical failure patterns.