eLLMulator
Agentic Distributed Trace Simulation
Traditional distributed tracing shows what happened at runtime but can't reason about intent or surface contract mismatches. eLLMulator takes a different approach: LLM agents become your software components. Each agent studies its assigned source file, then interacts with other agents via synchronous MCP tool calls that mirror real function calls. The call graph emerges naturally from code control flow, producing traces that capture not just what happened, but why each component behaved as it did.
- Client
- Open source
- Role
- Creator
- Duration
- 2025
- Team
- Solo
- •Source files become autonomous Claude agents
- •Agent communication mirrors real function calls via MCP
- •Five finding types including contract mismatches and assumption bugs
- •Three trace modes: Full, Targeted, and Lens
- •OpenTelemetry export to standard observability platforms
The approach
Each source file becomes an autonomous Claude agent. Agent-to-agent communication via MCP tool calls mirrors real function calls.
Five finding types: contract mismatches, assumption bugs, missing error paths, dead spots, unexpected calls. Three trace modes: Full, Targeted, and Lens.
Infrastructure
OpenTelemetry export to Jaeger, Tempo, or Honeycomb. Smart entry point detection from natural language scenarios.
Dependency graph (Starmap) with SCC clustering. Multi-layer guardrails: cycle detection, depth limiting, rate limiting, circuit breakers.