observe-metrics
Aggregate and display system metrics with anomaly detection for a time period
Profile →npx skills add ruvnet/ruflo --skill observe-metrics --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 Metrics Aggregate counters, gauges, and histograms from the observability namespace and flag anomalies. ## When to use When you need a snapshot of system health -- task completion rates, error rates, active agent counts, memory usage, and token consumption. Useful for monitoring swarm performance and detecting degradation. ## Steps 1. **Retrieve metrics** -- call `mcp__plugin_ruflo-core_ruflo__memory_search --namespace observability` (or `memory_list`) to fetch metric records for the specified period (default: 1 hour). The `memory_*` tool family routes by namespace; `agentdb_hierarchical-*` does NOT, so use `memory_*` here. 2. **Aggregate** -- compute: - Counters: sum totals (tasks_completed, errors, token_usage) - Gauges: current values (active_agents, memory_usage_bytes) - Histograms: p50, p95, p99 (task_duration_ms, span_duration_ms) 3. **Compute baselines** -- call `mcp__plugin_ruflo-core_ruflo__agentdb_pattern-search` (ReasoningBank-routed; **don't** pass a `namespace` argument — pattern-* tools ignore it) to establish baseline values for each metric. 4. **Flag anomalies** -- mark metrics deviating >2 standard deviations from baseline with direction (above/below) and
- When to use
- Steps
- CLI alternative
npx @claude-flow/cli@latest memory search --query "system metrics for last hour" --namespace observability
What does the observe-metrics skill do?
Aggregate and display system metrics with anomaly detection for a time period
How do I install it?
Run `npx skills add ruvnet/ruflo --skill observe-metrics --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.