description: > 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.
Session Report
Generate a detailed session report from the Claude Code Agent Monitor.
Input
The user provides: $ARGUMENTS
This may be a session ID, "latest", or a date range like "last 24 hours".
Data Sources
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 |
Key data points available per session
- Status:
active/completed/error/abandoned - Model: primary model (e.g.
claude-sonnet-4-20250514) - Metadata (JSON):
thinking_blockscount,turn_count,total_turn_duration_ms,usage_extras(service_tier, speed, inference_geo) - Token usage per model: Pricing breakdown reports
input_tokens,output_tokens,cache_read_tokens,cache_write_tokensper model (baselines are pre-summed into these totals at the DB level) - Cost formula:
(tokens / 1,000,000) × rate_per_mtokfor each of 4 token types, using longest-match pricing rule - Agent hierarchy: recursive parent_agent_id tree, subagent_type (e.g. "task", "explore", "code-review", "compaction")
- Event types:
PreToolUse,PostToolUse,Stop,SubagentStop,SessionStart,SessionEnd,Notification,Compaction,APIError,TurnDuration
Report Sections
1. Session Overview
- ID (first 16 chars), name, status, model, working directory
- Start → end time, total duration
- Turn count and avg turn duration (from metadata)
2. Token Usage (per model)
| Model | Input | Output | Cache Read | Cache Write | Total |
Show effective totals (current + baseline) since baselines preserve tokens lost during compaction. Calculate cache hit rate: cache_read / (cache_read + input) × 100.
3. Cost Breakdown
From /api/pricing/cost/{id} — show each model's cost with the matched pricing rule. Note rates are per million tokens.
4. Agent Hierarchy
Render the agent tree (main → subagents, with nested children). For each agent: name, type, subagent_type, status, task (first 60 chars), duration.
5. Tool Activity
Count PreToolUse events by tool_name. Flag tools that appear in error events. Note subagent spawns (tool_name = "Agent").
6. Compaction & Context Health
- Count of
Compactionevents (each = context was compressed) - Baseline tokens recovered (sum of baseline_* columns)
- Thinking block count from metadata
7. API Errors
List any APIError events with type (quota, rate_limit, overloaded) and message.
8. Timeline
Key lifecycle events: SessionStart → first tool → compactions → errors → Stop → SessionEnd. Include TurnDuration events.
Output Format
Clean Markdown: executive summary line, structured tables, agent tree, numbered timeline. Bold key metrics.