Observe Trace

Collect distributed trace spans for a task and build a visual trace tree showing the execution flow, timing, and bottlenecks.

When to use

When you need to understand how a task was executed across agents -- which spans ran, how long each took, where bottlenecks occurred, and how agents coordinated.

Steps

1. Collect spans -- call mcp__claude-flow__memory_search --namespace observability (or memory_list) to retrieve all spans matching the <task-id>. The memory_* tool family routes by namespace; agentdb_hierarchical-* does NOT (it routes by tier working|episodic|semantic), so use memory_* here. See ruflo-agentdb ADR-0001 §"Namespace convention".
2. Build trace tree -- organize spans into a parent-child hierarchy using parentSpanId references, with the root span at the top
3. Calculate timing -- for each span, compute duration (endTime - startTime), and identify the critical path (longest chain of sequential spans)
4. Identify bottlenecks -- flag spans where duration exceeds the p95 for that operation type, or where gaps between spans suggest idle time
5. Synthesize -- call mcp__claude-flow__agentdb_context-synthesize to combine span metadata into a narrative summary of the execution flow
6. Report -- display the trace tree with: span name, agent, duration, status (OK/ERROR), and bottleneck flag; include total trace duration and critical path duration

CLI alternative

npx @claude-flow/cli@latest memory search --query "trace spans for task TASK_ID" --namespace observability