Monitor your AI conversation health like a doctor checks vital signs. Auto-collection + Real-time dashboard + Actionable insights.
Before: Manual tracking for every turn
Now: One command, automatic tracking
bash
vitals start claude-sonnet-4.6
# All conversations tracked automatically!
Live terminal UI with health monitoring:
bash
vitals dashboard
Shows:
bash
# 1. Start monitoring (one command!)
vitals start claude-sonnet-4.6
# 2. View real-time dashboard (in another terminal)
vitals dashboard
# 3. Check status anytime
vitals status
# 4. Generate report when done
vitals report
CommandDescriptionvitals start [model]Start auto-monitoring sessionvitals dashboardLaunch real-time dashboardvitals statusShow current session statusvitals summaryQuick session summaryvitals completeMark session as completevitals reportGenerate detailed report
MetricDescriptionHealthyWarningDangerFirst-Try Success% tasks without rework≥70%50-70%<50%Rework CountCorrections per task01-2>2Promise Fulfillment% promises delivered≥80%60-80%<60%Plan InflationActual / Promised turns≤1.3x1.3-2.0x>2.0xToken EfficiencyValue per token≥0.150.08-0.15<0.08
ScoreStatusEmojiColor85-100Excellent🟢Green70-84Good🟡Yellow50-69Warning🟠Orange<50Critical🔴Red
text
📊 Chat Vitals Dashboard
──────────────────────────────────────────────────
Session: a1b2c3d4
Model: claude-sonnet-4.6
Started: 2026-04-08T11:34:27
Health Score:
🟢 85/100 - Excellent
[██████████████████████████████] 85%
Key Metrics:
──────────────────────────────────────────────────
✅ First-Try Success: 85%
✅ Rework Count: 0
⚠️ Promise Fulfillment: 75%
✅ Plan Inflation: 1.1x
✅ Token Efficiency: 0.22
Session Stats:
💬 Total Turns: 3
🔢 Total Tokens: 1,030
📊 Avg Tokens/Turn: 343
Edit ~/.openclaw/skills/chat-vitals/config.json:
json
{
"monitor": {
"token_thresholds": {
"report_daily": 50000
},
"health_thresholds": {
"first_try_success_rate": {
"excellent": 85,
"good": 70,
"warning": 50
}
}
},
"patterns": {
"correction_keywords": ["不对", "错了", "重新"],
"promise_patterns": ["接下来我会", "首先让我"]
}
}
text
chat-vitals/
├── vitals # ⭐ Simple CLI entry point
├── SKILL.md
├── README.md
├── config.json
├── scripts/
│ ├── collector.py # Core data collection
│ ├── analyzer.py # Metric analysis
│ ├── reporter.py # Report generation
│ ├── auto_collector.py # ⭐ Auto-collection
│ └── dashboard.py # ⭐ Real-time dashboard
└── tests/
└── test_vitals.py # Test suite
bash
cd ~/.openclaw/skills/chat-vitals
./tests/run_tests.sh
# Test new features
vitals start test-model
vitals status
vitals dashboard # In a real terminal
bash
python3 scripts/collector.py create ...
python3 scripts/collector.py record ...
python3 scripts/collector.py complete ...
python
from llmchat_vitals.scripts import auto_collector
# Start monitoring
auto_collector.auto_start_session("gpt-4")
# Record turn
auto_collector.auto_record_turn(user_input, model_output)
# Get live summary
summary = auto_collector.get_session_summary()
print(f"Health: {summary['health_score']}/100")
Issues and PRs welcome!
MIT License