AI-Powered Software Investigation Room
GhostTrace is an AI-powered software investigation platform that helps developers understand why a codebase became difficult to maintain, not just what is wrong with it.
Unlike traditional static analyzers that generate warnings and metrics, GhostTrace reconstructs the story of a software system by analyzing its architecture, dependencies, code structure, and engineering patterns through a team of specialized AI investigators.
The result is a forensic-style investigation report that identifies architectural decay, technical debt, risky engineering decisions, future failure points, and actionable recovery strategies.
Modern software systems slowly become harder to maintain because of:
- Technical debt accumulation
- Architectural drift
- Dependency sprawl
- Inconsistent engineering decisions
- Lack of historical context
Existing tools answer:
What is wrong?
GhostTrace answers:
How did we get here, and what happens next?
Think of GhostTrace as a software crime investigation room.
Instead of generating another lint report, GhostTrace:
- Collects evidence
- Reconstructs history
- Predicts future risks
- Challenges assumptions
- Generates recovery plans
Examines:
- Code quality
- Technical debt
- Architectural violations
- Dependency complexity
- Suspicious engineering patterns
Produces:
- Evidence report
- Architecture findings
- Debt indicators
Reconstructs:
- Repository evolution
- Architectural drift
- Dependency growth
- System degradation timeline
Produces:
- Timeline of events
- Escalation points
- Degradation narrative
Predicts:
- Future failures
- High-risk modules
- Dependency collapse risks
- Stability concerns
Produces:
- Risk forecasts
- Risk scores
- Failure predictions
flowchart TD
A[GitHub Repository]
A --> B[Repository Analyzer]
B --> C[Forensic Investigator]
B --> D[Software Historian]
B --> E[Risk Oracle]
C --> F[Evidence Board]
D --> F
E --> F
F --> G[Devils Advocate]
G --> H[Recovery Commander]
H --> I[Final Investigation Report]
sequenceDiagram
participant User
participant Forensic
participant Historian
participant Risk
participant Contradiction
participant Remediation
User->>Forensic: Analyze Repository
Forensic->>Historian: Share Findings
Historian->>Risk: Timeline Context
Risk->>Contradiction: Risk Assessment
Contradiction->>Remediation: Debate Results
Remediation->>User: Recovery Plan
flowchart LR
A[Repository]
--> B[Architecture Analysis]
B --> C[Evidence Collection]
C --> D[Timeline Reconstruction]
D --> E[Risk Prediction]
E --> F[Contradiction Analysis]
F --> G[Recovery Strategy]
G --> H[Investigation Report]
- Architecture analysis
- Dependency mapping
- Technical debt detection
- Complexity assessment
- Timeline reconstruction
- Architectural drift detection
- Evolution tracking
- Risk forecasting
- Failure prediction
- Stability analysis
- Refactoring recommendations
- Prioritized fixes
- Recovery roadmap
| Traditional Tools | GhostTrace |
|---|---|
| Detect issues | Investigates causes |
| Static reports | Narrative investigation |
| Present-state analysis | Historical reconstruction |
| Lists warnings | Explains engineering decisions |
| Finds problems | Predicts future failures |
- Why did this architecture become unstable?
- Which decisions caused technical debt?
- What subsystem is most likely to fail next?
- Which dependencies are creating risk?
- What should be fixed first?
- How serious is the long-term maintenance risk?
- Next.js
- React
- TypeScript
- TailwindCSS
- Framer Motion
- Multi-Agent Architecture
- LLM Reasoning
- Repository Intelligence Engine
- Architecture Analysis
- Risk Analysis
- Timeline Reconstruction
- Contradiction Framework
ghosttrace/
├── app/
│ ├── api/
│ └── page.tsx
│
├── agents/
│ ├── forensic.ts
│ ├── historian.ts
│ ├── risk.ts
│ ├── contradiction.ts
│ ├── remediation.ts
│ └── orchestrator.ts
│
├── components/
│ ├── WarRoom.tsx
│ ├── Timeline.tsx
│ ├── RiskPanel.tsx
│ ├── AgentCard.tsx
│ └── EvidenceBoard.tsx
│
├── lib/
├── hooks/
├── types/
└── public/
git clone https://github.com/VishakhaVB/ghosttrace-agents.gitnpm installnpm run devhttp://localhost:3000
- GitHub Commit Intelligence
- Pull Request Investigation
- Team Ownership Analysis
- Architectural Drift Visualization
- CI/CD Integration
- Multi-Repository Comparison
- Enterprise Engineering Health Dashboard
teams understand why a codebase became difficult to maintain and what should be done next.