Debug Visualizer

What is Debug Visualizer?

Debug Visualizer takes error messages, stack traces, and bug descriptions and turns them into visual diagrams — call stacks, data flow charts, state transition maps, and dependency graphs. Instead of reading through lines of logs, you see the structure of the problem, which makes it far easier to identify where things went wrong and why.

It's useful for engineers debugging production issues, tracing errors through distributed systems, or trying to explain a complex bug to a teammate. By converting raw log output into a structured visual, Debug Visualizer reduces the cognitive overhead of understanding unfamiliar codepaths or tracing failures across service boundaries.

How to Use Debug Visualizer

Getting Started

1. Click Debug Visualizer in the sidebar.
2. Paste your error message, full stack trace, or a description of the bug.
3. The agent will generate a visual representation and an explanation of what it shows.
4. Ask follow-up questions to explore specific parts of the trace, understand the root cause, or get suggestions for a fix.

Navigation

Debug Visualizer is found in the sidebar under Agents. After submitting a trace or error, the visualization appears inline in the chat alongside a written explanation. You can click into specific nodes in the diagram to ask the agent about that part of the execution flow, or continue the conversation to narrow in on the root cause.

Key Features

Visualization Tools

• Interactive stack trace visualization — Renders call stacks as layered diagrams so you can see the full execution path from entry point to error, with each frame labeled by function and file.
• Real-time state diagrams — Maps application state before, during, and after the error to help identify unexpected transitions that preceded the failure.
• Dependency graph exploration — Shows how modules, services, or functions relate to each other so you can trace where a failure propagates through the system.
• Timeline view — Reconstructs the sequence of events leading up to an error, useful for race conditions and async bugs where ordering matters.

Collaboration Features

• IDE integration — Paste directly from your IDE or terminal; the agent understands common formats from all major languages and frameworks without needing any reformatting.
• Shareable diagrams — The generated visualizations can be shared with teammates who weren't present when the error occurred, enabling faster collaborative debugging without requiring everyone to reproduce the issue locally.

Example Use Cases

Common Scenarios

• Trace a production error through microservices by pasting the distributed trace and seeing which service introduced the failure.
• Visualize race conditions by mapping concurrent operations on a timeline to see where two processes collide.

Advanced Scenarios

• Map ETL transformations to understand where a data pipeline drops records or produces unexpected output across multiple processing stages.
• Collaborative debugging — Share the generated diagram with a teammate who wasn't there when the error occurred, so they can get up to speed instantly without needing the full context of the original incident.

Tips for Best Results

Getting Better Output

• Include the full stack trace. Truncated traces make it harder to identify the origin of the error. Copy everything from your terminal or log viewer, including the outermost frames.
• Describe expected vs actual behavior. Telling the agent "this function should return a list but it returned null" gives it enough context to focus on the relevant part of the trace rather than treating every frame equally.
• Ask for root cause analysis. After the initial visualization, ask "what is the most likely root cause?" or "where in the call stack should I focus?" to get specific debugging guidance.

Common Mistakes to Avoid

• Avoid pasting only the final error line without the surrounding trace — the root cause is almost always several frames up from where the exception was raised.
• Don't limit your input to the stack trace alone. Including a brief description of what the code is supposed to do gives the agent the context it needs to distinguish a logic error from an infrastructure failure.