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claude-code

Claude-Code-Agent-Monitor session-debug

install
source · Clone the upstream repo
git clone https://github.com/hoangsonww/Claude-Code-Agent-Monitor
Claude Code · Install into ~/.claude/skills/
T=$(mktemp -d) && git clone --depth=1 https://github.com/hoangsonww/Claude-Code-Agent-Monitor "$T" && mkdir -p ~/.claude/skills && cp -r "$T/plugins/ccam-devtools/skills/session-debug" ~/.claude/skills/hoangsonww-claude-code-agent-monitor-session-debug && rm -rf "$T"
manifest: plugins/ccam-devtools/skills/session-debug/SKILL.md
source content

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