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Documentation Index

Fetch the complete documentation index at: https://docs.vivi.bot/llms.txt

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Tracing gives you a detailed, step-by-step record of how your agents process requests. Each trace captures the full execution path — tool calls, LLM invocations, retrieved context, and returned outputs — so you can debug failures, measure latency, and verify that your agents are behaving as intended. Tracing is designed for real-time and near-real-time inspection. Spans appear within seconds of execution, making it ideal for active debugging and development workflows. For aggregated, historical analysis of agent performance, see Reports instead.
Tracing captures live execution data and is best suited for debugging and testing. For trend analysis and operational reporting, use Agent Reports instead.

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What tracing captures

Each trace is composed of spans — individual units of work performed during a single agent run. Together, spans form a tree that reflects the full lifecycle of a request. Traces are organized into turns, where each turn represents one round of user input and agent response. Within a turn, you can see every model call, tool invocation, and sub-agent operation that took place.
Span typeWhat it shows
ModelLLM inference steps, including token counts and latency
ToolsTool calls made during the run (e.g., search_mcp_tool)
Sub-agentsNested agent invocations and their outputs
The Conversation Details panel alongside each trace shows the full message history for that conversation, broken down by human messages, AI messages, and sub-agent messages.

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Reading a trace

Traces are displayed as a hierarchical span tree. The root span represents the top-level agent invocation; child spans nest beneath it in the order they were executed. To inspect a trace:
  1. Select a trace from the trace list. Traces are labeled and include a timestamp and duration.
  2. Navigate turns using the turn selector at the top left. Each turn shows its total duration and token count.
  3. Expand spans by clicking any row in the span tree. Child spans (model calls, tool calls) nest under their parent.
  4. View span details in the center panel. Toggle between Preview (formatted) and Metadata (raw) views, and expand Input and Output to inspect the exact data passed to and returned from each step. Some spans may show No data available if input/output logging is not enabled.
  5. Copy identifiers using the Copy Trace ID or Copy Step ID buttons for use in support requests or cross-referencing logs. You can also Download JSON to export the full trace payload.

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Conversation Details

The Conversation Details panel on the right provides a human-readable view of the conversation alongside the trace. It shows:
  • Total messages across the conversation
  • A breakdown of message types: human, AI, and sub-agent
  • The full Conversation Messages thread, so you can see exactly what the user asked and how the agent responded at each turn
Use this panel to connect low-level span data to the actual user experience. If a span looks correct in the trace but the agent’s response was wrong, the conversation view helps identify where the output diverged from expectations.

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Best practices

  • Use tracing during development to confirm that tool calls are firing in the right order with the right inputs.
  • Check token counts per turn to catch unexpectedly large context windows that may affect latency or cost.
  • Inspect failed spans — errors surface inline in the span tree, with the failure point clearly marked.
  • Cross-reference with Conversation Insights when you need to connect execution-level data to customer experience outcomes like sentiment and resolution.
  • Download the JSON payload for complex traces to analyze span timing or share with your engineering team.