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Zhongwei Li
2025-11-30 08:46:56 +08:00
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#!/usr/bin/env python3
"""
Evaluator Event Tracking
Privacy-first anonymous telemetry for ClaudeShack skills.
Usage:
# Track a skill invocation
python track_event.py --skill oracle --event invoked --success true
# Track a metric
python track_event.py --skill guardian --metric acceptance_rate --value 0.75
# Track an error (type only, no message)
python track_event.py --skill summoner --event error --error-type FileNotFoundError
# Enable/disable telemetry
python track_event.py --enable
python track_event.py --disable
# View local events
python track_event.py --show-events
python track_event.py --summary
"""
import os
import sys
import json
import argparse
import hashlib
from datetime import datetime, timedelta
from pathlib import Path
from typing import Dict, List, Optional, Any
def find_evaluator_root() -> Path:
"""Find or create the .evaluator directory."""
current = Path.cwd()
while current != current.parent:
evaluator_path = current / '.evaluator'
if evaluator_path.exists():
return evaluator_path
current = current.parent
# Not found, create in current project root
evaluator_path = Path.cwd() / '.evaluator'
evaluator_path.mkdir(parents=True, exist_ok=True)
return evaluator_path
def load_config(evaluator_path: Path) -> Dict[str, Any]:
"""Load Evaluator configuration."""
config_file = evaluator_path / 'config.json'
if not config_file.exists():
# Create default config (telemetry DISABLED by default)
default_config = {
"enabled": False,
"anonymous_id": generate_anonymous_id(),
"send_aggregates": False,
"retention_days": 30,
"aggregation_interval_days": 7,
"collect": {
"skill_usage": True,
"performance_metrics": True,
"error_types": True,
"success_rates": True
},
"exclude_skills": [],
"github": {
"repo": "Overlord-Z/ClaudeShack",
"discussions_category": "Telemetry",
"issue_labels": ["feedback", "telemetry"]
}
}
with open(config_file, 'w', encoding='utf-8') as f:
json.dump(default_config, f, indent=2)
return default_config
try:
with open(config_file, 'r', encoding='utf-8') as f:
return json.load(f)
except (json.JSONDecodeError, OSError, IOError):
return {"enabled": False}
def save_config(evaluator_path: Path, config: Dict[str, Any]) -> None:
"""Save Evaluator configuration."""
config_file = evaluator_path / 'config.json'
try:
with open(config_file, 'w', encoding='utf-8') as f:
json.dump(config, f, indent=2)
except (OSError, IOError) as e:
print(f"Error: Failed to save config: {e}", file=sys.stderr)
sys.exit(1)
def generate_anonymous_id() -> str:
"""Generate a daily-rotating anonymous ID.
Returns:
Anonymous hash that rotates daily
"""
# Use date as salt for daily rotation
date_salt = datetime.now().strftime('%Y-%m-%d')
# Mix with random system identifier (not personally identifiable)
# Using just the date makes it truly anonymous - all users on same date have same ID
combined = f"{date_salt}"
return hashlib.sha256(combined.encode()).hexdigest()[:16]
def track_event(
evaluator_path: Path,
config: Dict[str, Any],
skill_name: str,
event_type: str,
success: Optional[bool] = None,
error_type: Optional[str] = None,
duration_ms: Optional[int] = None,
metadata: Optional[Dict[str, Any]] = None
) -> None:
"""Track a skill usage event.
Args:
evaluator_path: Path to .evaluator directory
config: Evaluator configuration
skill_name: Name of the skill
event_type: Type of event (invoked, error, etc.)
success: Whether the operation succeeded
error_type: Type of error (if applicable)
duration_ms: Duration in milliseconds
metadata: Additional anonymous metadata
"""
if not config.get('enabled', False):
# Telemetry disabled, skip silently
return
# Check if skill is excluded
if skill_name in config.get('exclude_skills', []):
return
# Build event
event = {
"event_type": f"{skill_name}_{event_type}",
"skill_name": skill_name,
"timestamp": datetime.now().isoformat(),
"session_id": config.get('anonymous_id', 'unknown'),
"success": success,
"error_type": error_type, # Type only, never error message
"duration_ms": duration_ms
}
# Add anonymous metadata if provided
if metadata:
event["metadata"] = metadata
# Append to events file (JSONL format)
events_file = evaluator_path / 'events.jsonl'
try:
with open(events_file, 'a', encoding='utf-8') as f:
f.write(json.dumps(event) + '\n')
except (OSError, IOError) as e:
# Fail silently - telemetry should never break the workflow
pass
def track_metric(
evaluator_path: Path,
config: Dict[str, Any],
skill_name: str,
metric_name: str,
value: float,
metadata: Optional[Dict[str, Any]] = None
) -> None:
"""Track a skill metric.
Args:
evaluator_path: Path to .evaluator directory
config: Evaluator configuration
skill_name: Name of the skill
metric_name: Name of the metric
value: Metric value
metadata: Additional anonymous metadata
"""
track_event(
evaluator_path,
config,
skill_name,
"metric",
metadata={
"metric_name": metric_name,
"value": value,
**(metadata or {})
}
)
def load_events(evaluator_path: Path, days: Optional[int] = None) -> List[Dict[str, Any]]:
"""Load events from local storage.
Args:
evaluator_path: Path to .evaluator directory
days: Optional number of days to look back
Returns:
List of events
"""
events_file = evaluator_path / 'events.jsonl'
if not events_file.exists():
return []
events = []
cutoff = None
if days:
cutoff = datetime.now() - timedelta(days=days)
try:
with open(events_file, 'r', encoding='utf-8') as f:
for line in f:
try:
event = json.loads(line.strip())
# Filter by date if cutoff specified
if cutoff:
event_time = datetime.fromisoformat(event['timestamp'])
if event_time < cutoff:
continue
events.append(event)
except json.JSONDecodeError:
continue
except (OSError, IOError):
return []
return events
def show_summary(events: List[Dict[str, Any]]) -> None:
"""Show summary of local events.
Args:
events: List of events
"""
if not events:
print("No telemetry events recorded")
return
print("=" * 60)
print("LOCAL TELEMETRY SUMMARY (Never Sent Anywhere)")
print("=" * 60)
print()
# Count by skill
by_skill = {}
for event in events:
skill = event.get('skill_name', 'unknown')
if skill not in by_skill:
by_skill[skill] = {'total': 0, 'success': 0, 'errors': 0}
by_skill[skill]['total'] += 1
if event.get('success') is True:
by_skill[skill]['success'] += 1
elif event.get('error_type'):
by_skill[skill]['errors'] += 1
# Print summary
for skill, stats in sorted(by_skill.items()):
print(f"{skill}:")
print(f" Total events: {stats['total']}")
print(f" Successes: {stats['success']}")
print(f" Errors: {stats['errors']}")
if stats['total'] > 0:
success_rate = (stats['success'] / stats['total']) * 100
print(f" Success rate: {success_rate:.1f}%")
print()
print("=" * 60)
print(f"Total events: {len(events)}")
print("=" * 60)
def main():
parser = argparse.ArgumentParser(
description='Privacy-first anonymous telemetry for ClaudeShack',
formatter_class=argparse.RawDescriptionHelpFormatter
)
parser.add_argument('--skill', help='Skill name')
parser.add_argument('--event', help='Event type (invoked, error, etc.)')
parser.add_argument('--success', type=bool, help='Whether operation succeeded')
parser.add_argument('--error-type', help='Error type (not message)')
parser.add_argument('--duration', type=int, help='Duration in milliseconds')
parser.add_argument('--metric', help='Metric name')
parser.add_argument('--value', type=float, help='Metric value')
parser.add_argument('--enable', action='store_true', help='Enable telemetry (opt-in)')
parser.add_argument('--disable', action='store_true', help='Disable telemetry')
parser.add_argument('--status', action='store_true', help='Show telemetry status')
parser.add_argument('--show-events', action='store_true', help='Show local events')
parser.add_argument('--summary', action='store_true', help='Show event summary')
parser.add_argument('--days', type=int, help='Days to look back (default: all)')
parser.add_argument('--purge', action='store_true', help='Delete all local telemetry data')
args = parser.parse_args()
# Find evaluator directory
evaluator_path = find_evaluator_root()
config = load_config(evaluator_path)
# Handle enable/disable
if args.enable:
config['enabled'] = True
config['anonymous_id'] = generate_anonymous_id()
save_config(evaluator_path, config)
print("✓ Telemetry enabled (anonymous, opt-in)")
print(f" Anonymous ID: {config['anonymous_id']}")
print(" No personally identifiable information is collected")
print(" You can disable anytime with: --disable")
sys.exit(0)
if args.disable:
config['enabled'] = False
save_config(evaluator_path, config)
print("✓ Telemetry disabled")
print(" Run with --purge to delete all local data")
sys.exit(0)
# Handle status
if args.status:
print("Evaluator Telemetry Status:")
print("=" * 60)
print(f"Enabled: {config.get('enabled', False)}")
print(f"Anonymous ID: {config.get('anonymous_id', 'Not set')}")
print(f"Send aggregates: {config.get('send_aggregates', False)}")
print(f"Retention: {config.get('retention_days', 30)} days")
# Count events
events = load_events(evaluator_path)
print(f"Local events: {len(events)}")
print("=" * 60)
sys.exit(0)
# Handle purge
if args.purge:
events_file = evaluator_path / 'events.jsonl'
if events_file.exists():
events_file.unlink()
print("✓ All local telemetry data deleted")
else:
print("No telemetry data to delete")
sys.exit(0)
# Handle show events
if args.show_events:
events = load_events(evaluator_path, args.days)
print(json.dumps(events, indent=2))
sys.exit(0)
# Handle summary
if args.summary:
events = load_events(evaluator_path, args.days)
show_summary(events)
sys.exit(0)
# Track event
if args.skill and args.event:
track_event(
evaluator_path,
config,
args.skill,
args.event,
args.success,
args.error_type,
args.duration
)
# Silent success (telemetry should be invisible)
sys.exit(0)
# Track metric
if args.skill and args.metric and args.value is not None:
track_metric(
evaluator_path,
config,
args.skill,
args.metric,
args.value
)
# Silent success
sys.exit(0)
parser.print_help()
sys.exit(1)
if __name__ == '__main__':
main()