Discover when you are most active and most productive with Claude Code by bucketing sessions and events into hour-of-day and day-of-week bins from their timestamps, then flagging peak versus low-output windows. Uses the session list, per-session events, and analytics daily trends. Use when planning a schedule or deciding when to do deep work versus lighter tasks.
インストールする前に、エージェントに与えられる指示の中身を確認できます。
Profile activity and productivity across the hours of the day and days of the week.
The user provides: $ARGUMENTS
This may be:
cwd| Endpoint | Returns |
|---|---|
GET /api/sessions?limit=500 | Sessions with started_at, ended_at, status, cwd, cost, and metadata (turn_count, total_turn_duration_ms) — primary source for hour/weekday bucketing |
GET /api/events?session_id=X | Events with timestamp and event_type (PreToolUse, PostToolUse, Stop, Compaction, APIError, etc.) — finer-grained activity within sessions and error timing |
GET /api/analytics | daily_sessions / daily_events (365d) and sessions_by_status for trend context and completion baselines |
Bucket sessions (by started_at) and events (by timestamp) into 24 hourly bins.
Show a text bar chart of session and event counts per hour. Identify the busiest
hours by raw volume.
For each hour bin, compute completion rate (completed / total sessions started in
that hour) and average sustained turn time
(total_turn_duration_ms / turn_count, ms → minutes). Distinguish "active" hours
(high volume) from "productive" hours (high completion + sustained turns).
Bucket the same metrics into 7 weekday bins. Table: weekday, sessions, completion rate, avg cost, dominant model.
/api/events event types
(APIError, Compaction) to corroborate.Suggest which hour/weekday blocks to reserve for deep work and which to use for lighter or shallower tasks, grounded in the buckets above.
09:00 ████████ 24) for the hourly
and weekday distributions.started_at or the focus metadata, noting the count.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。
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.
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。