Skill456 repo starsupdated 2d ago

session-debug

The session-debug skill queries Claude Code Agent Monitor data to inspect and analyze Claude Code sessions by session ID, recency, or error status. It retrieves comprehensive session metadata, event timelines, agent hierarchies, and tool execution traces from a local API, then produces a color-coded debug report identifying bottlenecks, failures, anomalies, and root causes with remediation suggestions.

View source Repository: Claude-Code-Agent-Monitor

Install in Claude Code

Copy

git clone --depth 1 https://github.com/hoangsonww/Claude-Code-Agent-Monitor /tmp/session-debug && cp -r /tmp/session-debug/plugins/ccam-devtools/skills/session-debug ~/.claude/skills/session-debug

Then start a new Claude Code session; the skill loads automatically.

Definition

SKILL.md

# Session Debug

Debug and inspect a Claude Code session from Agent Monitor data.

## Input

The user provides: **$ARGUMENTS**

This may be:
- A session ID to debug
- "latest" or "last" for the most recent session
- "errors" to find and debug the most recent errored session

## Procedure

1. **Identify the target session**:
   - If session ID given: `GET /api/sessions/{id}` from `http://localhost:4820`
   - If "latest": `GET /api/sessions?limit=1` (default sort: most recently updated first)
   - If "errors": `GET /api/sessions?limit=10&status=error`

2. **Collect full session data**:
   - Session metadata: status, model, cwd, timestamps, duration
   - Events: `GET /api/events?session_id={session_id}` — full event timeline
   - Agents: `GET /api/agents?session_id={session_id}` — all agents in session
   - Cost: `GET /api/pricing/cost/{session_id}`

3. **Analyze the session**:

   ### Session Lifecycle
   - Start time → first event → last event → end time
   - Status transitions (active → working → completed/error)
   - Total duration and active-vs-idle time

   ### Event Chain Analysis
   - Chronological event list with timestamps and durations
   - Identify the **critical path** (longest chain of dependent events)
   - Flag events that took unusually long
   - Highlight error events with full error context

   ### Agent Inspection
   - List all agents: type, task, status, duration
   - Subagent tree visualization (parent → children)
   - Agents that failed and their last known state
   - Agent switching patterns (when and why new agents spawned)

   ### Tool Execution Trace
   - Every tool invocation in order with: tool name, duration, success/failure
   - Failed tool calls with error messages
   - Tool retry patterns (same tool called multiple times)

   ### Anomaly Detection
   - Events out of expected order
   - Gaps in event timeline (>30s with no events)
   - Duplicate events or agent states
   - Token usage spikes (compaction indicators)

4. **Diagnosis**:
   - Root cause hypothesis (if errors present)
   - Contributing factors
   - Remediation suggestions

## Output Format

Present as a debug report with:
- Session summary header (ID, status, model, duration, cost)
- Color-coded timeline (✅ success, ❌ error, ⚠️ warning, ℹ️ info)
- Agent tree diagram
- Diagnosis section with numbered findings