Report concurrency and parallelism for a session — how many agents ran in parallel, concurrency-lane utilization, peak parallel width, and serialization bottlenecks (sequential chains that could have run as parallel lanes) — using the Agent Monitor workflow intelligence API. Use when checking whether a multi-agent session used parallelism efficiently.
The English summary is being prepared. Showing the original description.
See how to installReview the instructions the agent will receive before you install.
Report on parallel execution for one Claude Code session: lanes, peak width, utilization, and where work serialized.
The user provides: $ARGUMENTS
A session ID. If empty, fetch GET /api/sessions?limit=1 and report on the most recent session, stating which one.
| Endpoint | Returns |
|---|---|
GET /api/workflows/{sessionId} | The concurrency dataset (overlapping agent execution lanes with start/end timing) and the complexity dataset (numeric score from depth, breadth, and tool diversity) |
From concurrency: number of distinct lanes, peak parallel width (max agents running simultaneously), and total agents. Pair with the complexity score to judge whether the parallelism matched the work's size.
Lanes: N · Peak parallel: M · Agents: K · Complexity: S
A per-lane list of the agents that occupied each lane in order:
Lane 1: explore (0–12s) → code-review (12–48s)
Lane 2: debugger (5–30s)
Show overlapping windows so simultaneity is visible.
| Lane | Busy time | Idle time | Utilization % |
|---|---|---|---|
| Plus an overall utilization figure (busy lane-time / total lane-time). |
Identify sequential chains where one agent waited on the previous despite no apparent dependency — candidates to run as parallel lanes. State the chain and the wall-clock time it cost. Only flag chains the concurrency timing data actually shows as sequential.
48s, 2m 10s); percentages to whole numbers.npm start from the repo root.No reviews yet. Tell others what you thought.
No login needed. Share how it worked for you, ask a question, or note where it did not run.
No comments yet. Be the first to write one.
Inspect fired CCAM alerts and manage alert rules for token thresholds, event patterns, inactivity, and status duration. Use when acknowledging alerts, creating or editing a rule, checking cooldowns, or connecting alert rules to webhook targets.
The English summary is being prepared. Showing the original description.
Identify anomalous sessions using Agent Monitor data — cost outliers from the pricing engine, token anomalies (cache miss spikes, compaction baseline surges), unusual event type ratios (PreToolUse/PostToolUse gaps, APIError clusters), behavioral deviations from workflow intelligence (complexity score outliers, error propagation anomalies), and sessions with abnormal metadata (extreme turn_count, high thinking_blocks, zero turn_duration).
The English summary is being prepared. Showing the original description.
Produce a detailed report on APIError events from Agent Monitor data — counts over time, which sessions and models are affected, and the likely root cause (rate limits, overload/529, or context-window pressure) inferred from each event's summary and data payload. Use when API errors spike or when you need to explain why requests are failing.
The English summary is being prepared. Showing the original description.
Benchmark one session (or a small recent set) against the rolling average using Agent Monitor data — cost, total tokens, tool count, and workflow complexity score — and report where each metric lands as a percentile of the population. Tells you whether a session was normal, cheap, or an outlier. Use when judging whether a session was typical or out of band.
The English summary is being prepared. Showing the original description.
Define a spend budget for Claude Code and, optionally, create a cost alert rule that fires when usage crosses the limit, via POST /api/alerts/rules on the Agent Monitor dashboard. Reads current spend from /api/pricing/cost to size the budget sensibly and explains every rule field before writing. Use when setting a spend limit or wiring up a budget guardrail.
The English summary is being prepared. Showing the original description.
Analyze prompt-cache effectiveness for Claude Code usage from the Agent Monitor dashboard — cache hit rate (total_cache_read / (total_cache_read + total_input)), cache_write vs cache_read reuse, cache-read vs cache-write spend, and the sessions with the poorest reuse. Pulls token totals from /api/analytics, per-session detail from /api/sessions, and dollar splits from /api/pricing/cost. Use when diagnosing cache spend or deciding whether prompt caching is paying off.
The English summary is being prepared. Showing the original description.