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.
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Drill into APIError events: how many, when, where, and most likely why.
The user provides: $ARGUMENTS
This may be:
| Endpoint | Returns |
|---|---|
GET /api/analytics | event_types (total APIError count), daily_events (365d) — APIError volume and trend over time |
GET /api/events?session_id=X | Per-session event stream — each APIError carries summary, data, and timestamp used to classify the cause |
GET /api/sessions?limit=N | Sessions with id, model, started_at — attribute each error to a model and place it on the timeline |
From GET /api/analytics: total APIError count and its share of total_events. Use daily_events to chart APIErrors over the requested window and flag any day that spikes above the window mean.
For each session in scope, pull GET /api/events?session_id=X and collect APIError events. Group by session_id and, via GET /api/sessions, by model. Report the top affected sessions and which model accounts for the most errors.
Inspect each error's summary/data and bucket it:
Compaction events).summary.
Report the count and percentage in each bucket.List the most recent APIErrors with timestamp, session_id, model, classified cause, and a one-line summary excerpt.
session_id, model, timestamp, and summary values — never invent a cause not supported by the payload; bucket as "Other" when unclear.curl cannot reach http://localhost:4820, tell the user to start the dashboard with npm start from the repo root.まだレビューはありません。使ってみた感想をお寄せください。
概要と使いどころ
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.
日本語の概要は準備中です。原文の説明を表示しています。
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).
日本語の概要は準備中です。原文の説明を表示しています。
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.
日本語の概要は準備中です。原文の説明を表示しています。
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.
日本語の概要は準備中です。原文の説明を表示しています。
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.
日本語の概要は準備中です。原文の説明を表示しています。
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.
日本語の概要は準備中です。原文の説明を表示しています。