distributed-debugging-debug-trace

What it does

This skill enables AI agents to execute distributed debugging sessions by generating and managing trace data across multiple services. It specifically handles the coordination required to correlate events in a microservices architecture, allowing for deep inspection of system behavior over time.

When to use it

• Investigating latency spikes that appear to originate from interactions between several backend services.
• Tracing the flow of a specific request through a complex event-driven system to identify bottlenecks.
• Debugging race conditions or timing issues that are difficult to reproduce in isolated unit tests.
• Analyzing error logs scattered across different nodes to reconstruct a complete failure timeline.

Key capabilities

• Initiates distributed debugging sessions automatically.
• Generates comprehensive trace data for analysis.
• Coordinates tracing activities across multiple distinct services.
• Correlates events to provide a unified view of system execution.

Example prompts

• "Start a distributed debug session for the payment processing pipeline and show me the full trace."
• "Trace the request ID abc-123 through our microservices cluster to find where the timeout occurred."
• "Run a distributed debug trace on the user authentication service and highlight any latency anomalies."

Tips & gotchas

Ensure your infrastructure supports distributed tracing protocols (like OpenTelemetry) before relying on this skill, as it depends on existing telemetry data. For best results, provide specific request IDs or time ranges to narrow the scope of the generated traces.