observe-trace
Trace agent execution by collecting spans and building a trace tree for a task
Profile →npx skills add ruvnet/ruflo --skill observe-trace --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# 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__plugin_ruflo-core_ruflo__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"](../../../ruflo-agentdb/docs/adrs/0001-agentdb-optimization.md). 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. *
- When to use
- Steps
- CLI alternative
npx @claude-flow/cli@latest memory search --query "trace spans for task TASK_ID" --namespace observability
What does the observe-trace skill do?
Trace agent execution by collecting spans and building a trace tree for a task
How do I install it?
Run `npx skills add ruvnet/ruflo --skill observe-trace --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From ruvnet/ruflo, a repository with 67,015 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.