Add token usage analysis to subagent-driven-development test

- Rewrote analyze-token-usage.py to parse main session file correctly
- Extracts usage from toolUseResult fields for each subagent
- Shows breakdown by agent with descriptions
- Integrated into test-subagent-driven-development-integration.sh
- Displays token usage automatically after each test run

tests/claude-code/analyze-token-usage.py

@@ -0,0 +1,168 @@
+#!/usr/bin/env python3
+"""
+Analyze token usage from Claude Code session transcripts.
+Breaks down usage by main session and individual subagents.
+"""
+
+import json
+import sys
+from pathlib import Path
+from collections import defaultdict
+
+def analyze_main_session(filepath):
+    """Analyze a session file and return token usage broken down by agent."""
+    main_usage = {
+        'input_tokens': 0,
+        'output_tokens': 0,
+        'cache_creation': 0,
+        'cache_read': 0,
+        'messages': 0
+    }
+
+    # Track usage per subagent
+    subagent_usage = defaultdict(lambda: {
+        'input_tokens': 0,
+        'output_tokens': 0,
+        'cache_creation': 0,
+        'cache_read': 0,
+        'messages': 0,
+        'description': None
+    })
+
+    with open(filepath, 'r') as f:
+        for line in f:
+            try:
+                data = json.loads(line)
+
+                # Main session assistant messages
+                if data.get('type') == 'assistant' and 'message' in data:
+                    main_usage['messages'] += 1
+                    msg_usage = data['message'].get('usage', {})
+                    main_usage['input_tokens'] += msg_usage.get('input_tokens', 0)
+                    main_usage['output_tokens'] += msg_usage.get('output_tokens', 0)
+                    main_usage['cache_creation'] += msg_usage.get('cache_creation_input_tokens', 0)
+                    main_usage['cache_read'] += msg_usage.get('cache_read_input_tokens', 0)
+
+                # Subagent tool results
+                if data.get('type') == 'user' and 'toolUseResult' in data:
+                    result = data['toolUseResult']
+                    if 'usage' in result and 'agentId' in result:
+                        agent_id = result['agentId']
+                        usage = result['usage']
+
+                        # Get description from prompt if available
+                        if subagent_usage[agent_id]['description'] is None:
+                            prompt = result.get('prompt', '')
+                            # Extract first line as description
+                            first_line = prompt.split('\n')[0] if prompt else f"agent-{agent_id}"
+                            if first_line.startswith('You are '):
+                                first_line = first_line[8:]  # Remove "You are "
+                            subagent_usage[agent_id]['description'] = first_line[:60]
+
+                        subagent_usage[agent_id]['messages'] += 1
+                        subagent_usage[agent_id]['input_tokens'] += usage.get('input_tokens', 0)
+                        subagent_usage[agent_id]['output_tokens'] += usage.get('output_tokens', 0)
+                        subagent_usage[agent_id]['cache_creation'] += usage.get('cache_creation_input_tokens', 0)
+                        subagent_usage[agent_id]['cache_read'] += usage.get('cache_read_input_tokens', 0)
+            except:
+                pass
+
+    return main_usage, dict(subagent_usage)
+
+def format_tokens(n):
+    """Format token count with thousands separators."""
+    return f"{n:,}"
+
+def calculate_cost(usage, input_cost_per_m=3.0, output_cost_per_m=15.0):
+    """Calculate estimated cost in dollars."""
+    total_input = usage['input_tokens'] + usage['cache_creation'] + usage['cache_read']
+    input_cost = total_input * input_cost_per_m / 1_000_000
+    output_cost = usage['output_tokens'] * output_cost_per_m / 1_000_000
+    return input_cost + output_cost
+
+def main():
+    if len(sys.argv) < 2:
+        print("Usage: analyze-token-usage.py <session-file.jsonl>")
+        sys.exit(1)
+
+    main_session_file = sys.argv[1]
+
+    if not Path(main_session_file).exists():
+        print(f"Error: Session file not found: {main_session_file}")
+        sys.exit(1)
+
+    # Analyze the session
+    main_usage, subagent_usage = analyze_main_session(main_session_file)
+
+    print("=" * 100)
+    print("TOKEN USAGE ANALYSIS")
+    print("=" * 100)
+    print()
+
+    # Print breakdown
+    print("Usage Breakdown:")
+    print("-" * 100)
+    print(f"{'Agent':<15} {'Description':<35} {'Msgs':>5} {'Input':>10} {'Output':>10} {'Cache':>10} {'Cost':>8}")
+    print("-" * 100)
+
+    # Main session
+    cost = calculate_cost(main_usage)
+    print(f"{'main':<15} {'Main session (coordinator)':<35} "
+          f"{main_usage['messages']:>5} "
+          f"{format_tokens(main_usage['input_tokens']):>10} "
+          f"{format_tokens(main_usage['output_tokens']):>10} "
+          f"{format_tokens(main_usage['cache_read']):>10} "
+          f"${cost:>7.2f}")
+
+    # Subagents (sorted by agent ID)
+    for agent_id in sorted(subagent_usage.keys()):
+        usage = subagent_usage[agent_id]
+        cost = calculate_cost(usage)
+        desc = usage['description'] or f"agent-{agent_id}"
+        print(f"{agent_id:<15} {desc:<35} "
+              f"{usage['messages']:>5} "
+              f"{format_tokens(usage['input_tokens']):>10} "
+              f"{format_tokens(usage['output_tokens']):>10} "
+              f"{format_tokens(usage['cache_read']):>10} "
+              f"${cost:>7.2f}")
+
+    print("-" * 100)
+
+    # Calculate totals
+    total_usage = {
+        'input_tokens': main_usage['input_tokens'],
+        'output_tokens': main_usage['output_tokens'],
+        'cache_creation': main_usage['cache_creation'],
+        'cache_read': main_usage['cache_read'],
+        'messages': main_usage['messages']
+    }
+
+    for usage in subagent_usage.values():
+        total_usage['input_tokens'] += usage['input_tokens']
+        total_usage['output_tokens'] += usage['output_tokens']
+        total_usage['cache_creation'] += usage['cache_creation']
+        total_usage['cache_read'] += usage['cache_read']
+        total_usage['messages'] += usage['messages']
+
+    total_input = total_usage['input_tokens'] + total_usage['cache_creation'] + total_usage['cache_read']
+    total_tokens = total_input + total_usage['output_tokens']
+    total_cost = calculate_cost(total_usage)
+
+    print()
+    print("TOTALS:")
+    print(f"  Total messages:         {format_tokens(total_usage['messages'])}")
+    print(f"  Input tokens:           {format_tokens(total_usage['input_tokens'])}")
+    print(f"  Output tokens:          {format_tokens(total_usage['output_tokens'])}")
+    print(f"  Cache creation tokens:  {format_tokens(total_usage['cache_creation'])}")
+    print(f"  Cache read tokens:      {format_tokens(total_usage['cache_read'])}")
+    print()
+    print(f"  Total input (incl cache): {format_tokens(total_input)}")
+    print(f"  Total tokens:             {format_tokens(total_tokens)}")
+    print()
+    print(f"  Estimated cost: ${total_cost:.2f}")
+    print("  (at $3/$15 per M tokens for input/output)")
+    print()
+    print("=" * 100)
+
+if __name__ == '__main__':
+    main()

tests/claude-code/test-subagent-driven-development-integration.sh

@@ -277,6 +277,14 @@ else
 fi
 echo ""
 
+# Token Usage Analysis
+echo "========================================="
+echo " Token Usage Analysis"
+echo "========================================="
+echo ""
+python3 "$SCRIPT_DIR/analyze-token-usage.py" "$SESSION_FILE"
+echo ""
+
 # Summary
 echo "========================================"
 echo " Test Summary"