This skill generates a detailed session report from the Claude Code Agent Monitor, including per-model token usage, cost breakdown, tool invocations, agent hierarchy, compaction events, API errors, turn durations, and thinking block counts. It solves the problem of aggregating and presenting complex session data into a structured report. An agent or developer should use it when reviewing a specific session or summarizing activity over a date range, using a session ID, "latest", or a date range as input.
Resources
1Install
npx skillscat add hoangsonww/claude-code-agent-monitor/session-report Install via the SkillsCat registry.
This skill generates a detailed session report from the Claude Code Agent Monitor, including per-model token usage, cost breakdown, tool invocations, agent hierarchy, compaction events, API errors, turn durations, and thinking block counts. It solves the problem of aggregating and presenting complex session data into a structured report. An agent or developer should use it when reviewing a specific session or summarizing activity over a date range, using a session ID, "latest", or a date range as input.
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)
Include 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.
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.