tldr-stats

# TLDR Stats Skill Show a beautiful dashboard with token usage, actual API costs, TLDR savings, and hook activity. ## When to Use - See how much TLDR is saving you in real $ terms - Check total session token usage and costs - Before/after comparisons of TLDR effectiveness - Debug whether TLDR/hooks are being used - See which model is being used ## Instructions **IMPORTANT:** Run the script AND display the output to the user. 1. Run the stats script: ```bash python3 $CLAUDE_PROJECT_DIR/.claude/scripts/tldr_stats.py ``` 2. **Copy the full output into your response** so the user sees the dashboard directly in the chat. Do not just run the command silently - the user wants to see the stats. ### Sample Output ``` ╔══════════════════════════════════════════════════════════════╗ ║ 📊 Session Stats ║ ╚══════════════════════════════════════════════════════════════╝ You've spent $96.52 this session Tokens Used 1.2M sent to Claude 416.3K received back 97.8K from prompt cache (8% reused) TLDR Savings You sent: 1.2M Without TLDR: 2.5M 💰 TLDR saved you ~$18.83 (Without TLDR: $115.35 → With TLDR: $96.52) File reads: 1.3M → 20.9K █████████░ 98% smaller TLDR Cache Re-reading the same file? TLDR remembers it. █████░░░░░░░░░░ 37% cache hits (35 reused / 60 parsed fresh) Hooks: 553 calls (✓ all ok) History: █▃▄ ▇▃▇▆ avg 84% compression Daemon: 24m up │ 3 sessions ``` ## Understanding the Numbers | Metric | What it means | |--------|---------------| | **You've spent** | Actual $ spent on Claude API this session | | **You sent / Without TLDR** | Actual tokens vs what it would have been | | **TLDR saved you** | Money saved by compressing file reads | | **File reads X → Y** | Raw file tokens compressed to TLDR summary | | **Cache hits** | How often TLDR reuses parsed file results | | **History sparkline** | Compression % over recent sessions (█ = high) | ## Visual Elements - **Progress bars** show savings and cache efficiency at a glance - **Sparklines** show historical trends (█ = high savings, ▁ = low) - **Colors** indicate status (green = good, yellow = moderate, red = concern) - **Emojis** distinguish model types (🎭 Opus, 🎵 Sonnet, 🍃 Haiku) ## Notes - Token savings vary by file size (big files = more savings) - Cache hit rate starts low, increases as you re-read files - Cost estimates use: Opus $15/1M, Sonnet $3/1M, Haiku $0.25/1M - Stats update in real-time as you work