tldr-stats

• 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

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

```

1. 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

```

| 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) |

• 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)

• 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