| name | model_usage |
| description | Track and display LLM token usage, costs, and model statistics. Use when: user asks about token usage, API costs, how many messages were sent, or model performance stats. NOT for: changing the model or provider (use change_setting), or viewing conversation content (use session_logs). |
| metadata | {"emoji":"📈"} |
Model Usage
Track and display LLM token usage, costs, and session statistics.
When to Use
✅ USE this skill when:
- "How many tokens have I used?"
- "What's my API cost so far?"
- "Show me model usage stats"
- "How many messages in this session?"
- "Which model am I using?"
When NOT to Use
❌ DON'T use this skill when:
- Changing the LLM model or provider → use
change_setting
- Viewing conversation content → use
session_logs
- Checking system status → check agent status directly
Usage
Current session stats
python {skill_path}/usage_stats.py
Check detailed interaction log
The history_detail.jsonl file under ~/.pythonclaw/context/logs/ contains
structured records of every agent interaction, including:
- Input messages
- Tool calls and results
- LLM responses
- Timestamps
python {skill_path}/usage_stats.py --log ~/.pythonclaw/context/logs/history_detail.jsonl
Quick stats via jq (if installed)
wc -l ~/.pythonclaw/context/logs/history_detail.jsonl
tail -5 ~/.pythonclaw/context/logs/history_detail.jsonl | python -m json.tool
Notes
- Token counts are estimates based on message length
- Cost calculation requires knowing the model's pricing (not tracked automatically)
- The
history_detail.jsonl is append-only and grows over time
- Use
/status command in chat for quick session info
Resources
| File | Description |
|---|
usage_stats.py | Parse and summarise usage from history logs |
