Generate a comprehensive session report with per-model token usage (input, output, cache_read, cache_write including compaction baselines), cost breakdown via the pricing engine, tool invocations, agent hierarchy, compaction events, API errors, turn durations, and thinking block counts. Use when reviewing a specific session or summarizing activity over a date range.
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Generate a detailed session report from the Claude Code Agent Monitor.
The user provides: $ARGUMENTS
This may be a session ID, "latest", or a date range like "last 24 hours".
All data comes from the Agent Monitor API at http://localhost:4820:
| Endpoint | What it returns |
|---|---|
GET /api/sessions/{id} | Session with nested .agents[] and .events[] |
GET /api/sessions?limit=50 | Session list with agent_count, last_activity, and inline cost per session (bulk pricing applied server-side) |
GET /api/pricing/cost/{sessionId} | { total_cost, breakdown: [{ model, input_tokens, output_tokens, cache_read_tokens, cache_write_tokens, cost, matched_rule }] } |
GET /api/events?session_id={id} | Event stream: each has event_type, tool_name, summary, data (JSON), created_at |
active / completed / error / abandonedclaude-sonnet-4-20250514)thinking_blocks count, turn_count, total_turn_duration_ms, usage_extras (service_tier, speed, inference_geo)input_tokens, output_tokens, cache_read_tokens, cache_write_tokens per model (baselines are pre-summed into these totals at the DB level)(tokens / 1,000,000) × rate_per_mtok for each of 4 token types, using longest-match pricing rulePreToolUse, PostToolUse, Stop, SubagentStop, SessionStart, SessionEnd, Notification, Compaction, APIError, TurnDurationInclude these columns: Model, Input, Output, Cache Read, Cache Write, and Total.
Show effective totals (current + baseline) since baselines preserve tokens lost during compaction. Calculate cache hit rate: cache_read / (cache_read + input) × 100.
From /api/pricing/cost/{id} — show each model's cost with the matched pricing rule. Note rates are per million tokens.
Render the agent tree (main → subagents, with nested children). For each agent: name, type, subagent_type, status, task (first 60 chars), duration.
Count PreToolUse events by tool_name. Flag tools that appear in error events. Note subagent spawns (tool_name = "Agent").
Compaction events (each = context was compressed)List any APIError events with type (quota, rate_limit, overloaded) and message.
Key lifecycle events: SessionStart → first tool → compactions → errors → Stop → SessionEnd. Include TurnDuration events.
Clean Markdown: executive summary line, structured tables, agent tree, numbered timeline. Bold key metrics.
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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.
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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).
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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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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.
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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.
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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.
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